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    • 专利摘要:
    The invention relates to a method for processing (50) a signal from a coherent lidar comprising a coherent source (L) periodically modulated in frequency, -a beat signal (Sb) being generated by a photodetector (D) at from the interference between an optical signal called local oscillator having a local oscillator frequency (fOL (t)) and an optical signal backscattered by a target (T) illuminated by the lidar, said beat signal being digitized, -the local oscillator frequency (fOL (t)) consisting of the sum of a mean value (f0) and a modulation frequency (fmod (t)) resulting from the modulation of the source, the modulation frequency being periodic period according to a modulation period (TFO), each period comprising n linear portions respectively having n frequency slopes (αi), n being greater than or equal to 2, the method comprising the steps of: -modulating (501) in a complex manner the beat signal (Sb), -demodulating (502) the modulated signal (Smod) in complex manner by n demodulation frequencies (fdemod (i)) each having a single slope equal to the frequency slope (ai) of the frequency modulator (fmod), to obtain n demodulated signals (Sdemod (i)), -determine (503) n spectral densities (SP (i)) of the n demodulated signals (Sdemod (i)). -determining (504) n characteristic frequencies (vαi) -determining (505) a velocity information (v) and a distance information (d) of the target (T) from said n characteristic frequencies (Vαi).
    公开号:FR3055424A1
    申请号:FR1601251
    申请日:2016-08-23
    公开日:2018-03-02
    发明作者:Patrick Feneyrou；Gregoire Pillet
    申请人:Thales SA；
    IPC主号:
    专利说明:

    (57) The invention relates to a method of processing (50) a signal from a coherent lidar comprising a coherent source (L) modulated periodically in frequency,
    -a beat signal (Sb) being generated by a photodetector (D) from the interference between an optical signal called local oscillator having a local oscillator frequency (ÎolO)) and an optical signal backscattered by a target (T ) illuminated by the lidar, said beat signal being digitized,
    the local oscillator frequency (foL (t)) consisting of the sum of an average value (fO) and a modulation frequency (f word j (t)) resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period (T F0 ), each period comprising n linear parts respectively having n frequency slopes (ai), n being greater than or equal to 2, the method comprising the steps consisting in:
    -modulating (501) in a complex way the beat signal (Sb),
    demodulating (502) in a complex manner the modulated signal (S mod j by n demodulation frequencies (fdemodO)) each having a single slope equal to the frequency slope (ai) respective to the modulation frequency (fmod), to obtain n demodulated signals (S demoçJ (i)),
    -determine (503) n spectral densities (SP (i)) of the n demodulated signals (Sdemod (Ü) ·
    -determine (504) n characteristic frequencies (v ai )
    determining (505) speed information (v) and distance information (d) of the target (T) from said n characteristic frequencies (V ai ).
    fûL (t! = îo + f n

    Method for processing a signal from a coherent lidar and associated lidar system
    FIELD OF THE INVENTION
    The invention relates to the field of coherent frequency-modulated lidars used for example for long-range target detection.
    STATE OF THE ART
    The principle of a coherent lidar is well known from the state of the art and illustrated in FIG. 1. A coherent lidar comprises a coherent source L, typically a laser which emits a coherent light wave (near, visible or UV range), a device for transmitting DE which makes it possible to illuminate a volume of space, and a device for receiving DR, which collects a fraction of the light wave backscattered by a target T. The frequency shift Doppler vd op of the backscattered wave is a function of the radial speed v of the target T.
    On reception, a mixture is made between the received backscattered light wave S of frequency fs and a part of the transmitted wave called the OL wave for "local oscillator". The interference of these two waves is detected by a photodetector D, and the electrical signal at the output of the detector has an oscillating term called the beat signal Sb, in addition to the terms proportional to the received power and the local oscillator power. A processing unit UT digitizes this signal and extracts the speed information v from the target T.
    Preferably, the processing unit electronically filters the beat signal Sb in a narrow band centered on the zero frequency, in the absence of frequency offset (see below).
    For coherent lidars, the transmitting and receiving devices preferentially use the same optic (monostatic lidar). This characteristic makes it possible to obtain good mechanical stability and to reduce the influence of atmospheric turbulence at long distance, the paths of propagation of the incident and backscattered waves being combined.
    One solution for telemetry / velocimetry by lidar is to realize a frequency modulation system. This technique, conventional in radar, is of particular interest at present given the progress of fiber laser sources. Thanks to frequency modulation, a time / frequency analysis makes it possible to ascertain the distance d from the target and its speed v. This type of lidar also makes it possible to perform a laser anemometry function.
    An example of the optical architecture of a frequency-modulated lidar 20 is described in FIG. 2. The coherent source is frequency-modulated so that the frequency of the local oscillator is modulated according to a predetermined function called the waveform. whose control is ensured by the WFC module, synchronized with the UT processing unit.
    The optical signal on transmission is amplified by an EDFA amplifier, the transmission and reception use the same optic O and are separated using a circulator C. This optical signal can optionally be shifted in frequency, for example using an acousto-optical modulator which is preferably positioned before the EDFA amplifier but can also be positioned on the path of the local oscillator. In this case the electronic filtering in the processing unit is carried out around the offset frequency. A delay line LR makes it possible to equalize the optical paths of the local oscillator and of the transmission signal so as to filter, in the RF domain, the faults of the optical components placed after the EDFA amplifier (cross-talk fault of circulator C, imperfections in anti-reflection treatments of the emission / reception optics O, ...).
    An example of a coherent frequency-modulated lidar is described in the document "Lidar Systems for precision navigation and safe landing on planetary bodies" Farzin Amzajerdian et al, Proc. SPIE 8192, International Symposium on Photoelectronic Detection and Imaging 2011: Laser Sensing and Imaging; and Biological and Medical Applications of Photonics Sensing and Imaging, 819202 (August19, 2011). Figure 3 describes the operating principle of this lidar.
    We place ourselves in the description below in the case where the optical emission frequency and that of the local oscillator are not offset using an acousto-optical modulator. The frequency of the local oscillator foL is linearly modulated according to two slopes of frequency a 0 and ai periodically with period T F0 . This optical frequency f OL can be written as the sum of a constant optical frequency fO (here the initial frequency of the laser) and a modulation frequency in the radio frequency domain dependent on time f mO d (t) resulting from the modulation of the laser source: f OL (t) = f0 + fmod (t)
    FIG. 3 illustrates the variation over time of the frequencies faith_ (t) and f s (t), the optical frequency f0 having been subtracted for greater clarity. As illustrated in FIG. 3a, the backscattered signal of frequency fs (t) is time-shifted by a time τ due to the propagation to the measurement area (target T) and therefore linked to the distance from the target d , and is shifted in frequency by a value vd op due to the Doppler effect with respect to the local oscillator frequency faith_ (t).
    The detected beat signal Sb has a frequency component fs-foL. FIG. 3b illustrates the evolution over time of fs -f 0L . It can be seen that this frequency difference comprises, as a function of time, two series of plates at the characteristic frequencies v a o and ν α · ι, directly related to the distance from the target D and to its speed v radial by the equations:
    2v 2a.nD. 2v 2a, D v = ---— and = --- i— “” λ c “> λ c
    By measuring these two characteristic frequencies v a0 and v a1 of the beat signal Sb, for example by carrying out a Fourier transform of this, we go back to d and v.
    However, when the distance to the target leads to a flight time greater than the duration of the waveform T F o normalized by the number of frequency slopes (2 in the example), the direct analysis by transform of Fourier is insufficient. Indeed, the mixture of the local oscillator and the backscattered signal leads to the disappearance of the plates and to a constantly variable instantaneous frequency, which after analysis by Fourier transform, will not present any peak.
    An example of this effect is illustrated in FIG. 4, for a modulation of the local oscillator according to two frequency slopes at 0 = 2 MHz / ps and α-ι = - 2 MHz / ps, and a target moving at the speed of 30 m / s.
    Figure 4a illustrates the temporal variation of fs with respect to îol and the frequency component of Sb fs-f OL for a distance d of 1800m, Figure 4b for a distance d of 14000 m and Figure 4c for a distance d of 20,000 m.
    In this case the range of the lidar is therefore limited by the signal processing whatever the power of the laser. It is theoretically possible to lengthen the modulation period T F o of the waveform, but the modulation range of certain lasers being limited, this lengthening does not make it possible to simultaneously achieve a high resolution at long distance. Indeed, given the limited modulation band of the laser, it is possible to increase the period T F o by reducing the frequency slopes to cover the same modulation band. In this case, the frequency plateaus will exist at a longer distance but, for a Fourier transform duration T FF t constant and less than the modulation frequency T F0 , the modulation band covered during T FFT will be less and therefore, the longitudinal resolution, proportional to this band, will be degraded.
    An object of the present invention is to remedy the aforementioned drawbacks by proposing a method of processing the beat signal making it possible to overcome this limitation by finding a signal having the characteristic frequency plateaus.
    DESCRIPTION OF THE INVENTION
    The present invention relates to a method of processing a signal from a coherent lidar comprising a coherent source modulated periodically in frequency,
    a beat signal being generated by a photodetector from the interference between an optical signal called a local oscillator having a local oscillator frequency and an optical signal backscattered by a target illuminated by the lidar, said beat signal being digitized,
    the local oscillator frequency consisting of the sum of an average value and a modulation frequency resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period, each period comprising n linear parts having respectively n frequency slopes, n being greater than or equal to 2, the method comprising the steps of;
    complex modulation of the beat signal by the modulation frequency to obtain a modulated signal,
    complex demodulation of the signal modulated by n demodulation frequencies each having a unique slope equal to the respective frequency slope of the modulation frequency, in order to obtain n demodulated signals,
    -determine n spectral densities of the n demodulated signals,
    -determine n characteristic frequencies corresponding respectively to the maximum of the n spectral densities,
    -determine speed information and target distance information from said n characteristic frequencies.
    According to one embodiment, the step of determining each spectral density comprises the sub-steps consisting in:
    -determine a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the modulation period,
    -determining said spectral density from the sum of the plurality of elementary spectral densities.
    Preferably, each elementary spectral density is determined by fast Fourier transform or FFT, and in which the spectral density is equal to an average of the elementary spectral densities.
    Advantageously, each demodulation frequency is periodic according to the modulation period.
    Advantageously, the frequency slopes are indexed by an index i varying from 0 to n − 1 and in which each demodulation frequency having a slope of index i is temporally offset with respect to the modulation frequency of a shift time dependent on i, n and the modulation period.
    According to a variant, the waveform comprises 4 slopes αθ, a1, a2, a3 with: α1 = - αθ and a3 = - a2
    The invention also relates to a coherent lidar system comprising:
    - a coherent source modulated periodically in frequency,
    a device for transmitting an optical signal from the coherent source and a device for receiving a signal backscattered by a target illuminated by the lidar,
    - a photodetector configured to generate a beat signal from the interference between an optical signal called a local oscillator having a local oscillator frequency and the backscattered optical signal, the local oscillator frequency being made up of the sum of a mean value and of a modulation frequency resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period, each period comprising n linear parts respectively having n frequency slopes, n being greater than or equal to 2,
    -a processing unit configured for:
    * digitize the beat signal, * complex modulate the beat signal by the modulation frequency to obtain a modulated signal, * complex demodulate the signal modulated by n demodulation frequencies each having a unique slope equal to the slope of respective frequency of the modulation frequency to obtain n demodulated signals, * determine n spectral densities of the n demodulated signals, * determine n characteristic frequencies corresponding respectively to the maximum of the n spectral densities, * determine speed information and distance information of the target from said n characteristic frequencies.
    Preferably, the processing unit is further configured to determine, for each spectral density, a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the modulation period, said spectral density being determined from the sum of the plurality of elementary spectral densities.
    Advantageously, each elementary spectral density is determined by fast Fourier transform, and in which the spectral density is equal to an average of the elementary spectral densities.
    Advantageously, the processing unit comprises n channels, one channel per slope, each channel operating in parallel with the others and being configured to determine the associated frequency.
    Other characteristics, objects and advantages of the present invention will appear on reading the detailed description which follows and with reference to the appended drawings given by way of nonlimiting examples and in which:
    Figure 1 already cited describes the principle of a coherent lidar.
    FIG. 2, already cited, describes an example of the optical architecture of a frequency modulation lidar.
    FIG. 3a, already cited, illustrates the variation over time of the frequencies faith_ (t) and f s (t). FIG. 3b, already cited, illustrates the evolution over time of fs -f 0L .
    FIG. 4a, already cited, illustrates the temporal variation of fs with respect to isol and the frequency component of Sb fs-f 0L for a distance d of 1800 m, FIG. 4b for a distance d of 14000 m and FIG. 4c for a distance d of 20,000 m.
    FIG. 5 illustrates the method of processing the signal from a coherent lidar according to the invention.
    FIG. 6 diagrams the periodic waveform of a modulation frequency f mO d (t) as a function of time, consisting of a series of 4 slopes αθ, a1, a2 and a3.
    Figure 7 illustrates the case of a target moving with a speed of 40 m / s at a distance of 12km, the waveform of the signal f mO d comprising 2 slopes αθ = 0.2 MHz / ps and a1 = -0.2 MHz / ps for an average laser frequency of 1.55 pm.
    FIG. 7a illustrates the variation as a function of time of the frequency of the local oscillator faith_ (t) and of the signal frequency fs (t). Figure 7b illustrates the two frequency components of the lidar beat signal Sb, fs-foL and foL-fs. FIG. 7c illustrates the variation as a function of time of the frequency of the modulated signal obtained S moc i. Figures 7d and 7e respectively illustrate the variation as a function of time of the demodulation frequencies fmod (0) (slope αθ) and f mO d (1) (slope a1). Figures 7f and 7g respectively illustrate the variation as a function of time of the demodulated signal S demod (0) and S dem od (1)
    FIG. 8 illustrates the spectral densities SP (0) (FIG. 8a) and SP (1) (FIG. 8b) of the spectra determined from the signals S dem od (0) and S demod (1).
    Figure 9 is equivalent to Figure 7 but for a target located at a distance of 18 km. FIG. 9a illustrates the variation as a function of time of the frequency of the local oscillator faith_ (t) and of the signal frequency fs (t). Figure 9b illustrates the two frequency components of the lidar beat signal Sb, fs-foL and foL-fs. FIG. 9c illustrates the variation as a function of time of the frequency of the modulated signal obtained S mO d- FIGS. 9d and 9e respectively illustrate the variation as a function of time of the demodulation frequencies f mO d (0) (slope αθ) and f mO d (1) (slope a1). Figures 9f and 9g respectively illustrate the variation as a function of time of the demodulated signal S dem od (0) and S demO d (1)
    FIG. 10a illustrates the variation over time of the frequencies faith (t) and f s (t) and FIG. 10b illustrates the evolution over time of fs -f 0 L for the case where f mo d has 4 slopes .
    FIG. 11a illustrates the variation over time of the frequencies faith_ (t) and f s (t), FIG. 11b illustrates the two frequency components of the lidar beat signal Sb, fs-foL and foL-fs, FIG. 11c illustrates the variation as a function of time of the frequency of the modulated signal obtained S mod for a waveform comprising 4 slopes.
    Figures 12a, 12b, 12c and 12d respectively illustrate the variation as a function of time of the demodulation frequencies f mO d (0) (slope αθ) and fmod (1) (slope a1), f mO d (2) (slope a2 ) and f mO d (3) (slope a3), and Figures 12e, 12f, 12g and 12h respectively illustrate the variation as a function of time of the demodulated signal S of mod (0) i S d emod (”i), S dem od (2) and S of mod (3).
    Figure 13 shows schematically a lidar system according to the invention.
    FIG. 14 illustrates an example of implementation of a parallel architecture of the lidar processing unit according to the invention.
    DETAILED DESCRIPTION OF THE INVENTION
    The method of processing 50 of the signal from a coherent lidar according to the invention is described in FIG. 5. The coherent lidar comprises a coherent source L modulated periodically according to an RF signal. RF modulation can be performed directly by the laser injection current or by an external component. By RF is meant a wave having a frequency between 1 Hz and 10 GHz, and preferably between 0.1 kHz and 10 MHz.
    A beat signal Sb is generated by a photodetector D from the interference between an optical signal, called local oscillator OL having a local oscillator frequency faith_ (t), and an optical signal fs (t) backscattered by an illuminated target T by the lidar. The beat signal is digitized for processing.
    The local oscillator frequency faith_ (t) consists of the sum of an average value fO and a modulation frequency f mO d (t) resulting from the modulation of the source.
    f 0L (t) = fo + fmod (t)
    When no acoustic offset modulator is used, the frequency fO is equal to the initial optical frequency of the source L. When the signal OL is shifted in frequency by an acousto-optical modulator, the frequency fO is equal to the frequency optical source shifted.
    The modulation frequency f mO d (t) is periodic according to a modulation period T F o, and comes from the periodic RF modulation of the source, but is not equivalent to the latter, due to the nonlinear behavior of the laser. . Typically the period T FO is between 1 ns and one second, and preferably between 100 ns and 10 ms.
    For the method according to the invention to work correctly, the modulation frequency f mO d (t) must be such that each period comprises n linear parts, ie n slopes of frequency ai, with i index varying from 0 to n-1, which join according to summits. The number of slopes n is greater than or equal to 2.
    Advantageously, n is even, because, as specified below, this makes it possible to alternate the signs of the slopes ai and thus simplify the signal processing.
    In practice, given the modulation frequency band accessible for current lasers, it is difficult to obtain acute angles for these vertices, and these are generally rounded, as illustrated in FIG. 6 for a frequency f mO d (t ) consisting of a series of 4 slopes αθ, a1, a2 and a3. The shape of the modulation signal of f mO d over a period T F o is called waveform.
    Preferably, the slope of index i + 1 a i + i has a sign opposite to the slope of index i ai. This makes it possible to reduce the frequency band covered by maintaining the same fraction of the period T F o for each slope (and therefore the same order of magnitude of intensity of the lines for each frequency slope).
    Preferably, the slopes of odd indices are equal to the opposite of the slopes of even index.
    For a signal f mO d with two slopes α1 = -αθ
    For a signal f mO d with four slopes α1 = -αθ and a3 = -a2
    In the latter case, the waveform can be divided into four equal parts (leading to four lines of close intensity) without using frequency discontinuities.
    Preferably, the slopes ai are between 0.1 MHz / ps and a few hundred MHz / ps.
    Note that it is not easy to obtain a local oscillator optical frequency modulated according to a series of predetermined linear slopes as illustrated in FIG. 6. For this it is necessary to pre-correct the RF signal for modulating the source, as for example described in patent application FR No. 1500603. For the application of the invention, the waveform of f mO d is assumed to be known with good accuracy.
    Before describing the steps of method 50 according to the invention, we will specify the terminology used.
    Modulation is the operation of adding a frequency to an initial signal and demodulation is the operation of subtracting a frequency from the initial signal. Thus modulating at + f is equivalent to demodulating at -f and vice versa.
    In time space, modulation or demodulation consists in multiplying an initial time signal SO (t) by a number, which is a real number for real modulation / demodulation (a cosine) and a complex number for modulation / complex demodulation.
    For example, modulating in a complex way by a frequency f is equivalent to multiplying SO (t) by exp (2jnÎt). Similarly, demodulating in a complex way by a frequency f is equivalent to multiplying SO (t) by exp (-2jnft).
    When the frequency f (t) is a function of time, it is necessary to multiply by exp for a modulation and by exp l
    - 2y π J f (ujdii for a demodulation.
    The method 50 according to the invention consists in a specific digital processing of a signal coming from a coherent lidar, for the determination of the information in speed and in distance of a target illuminated by the lidar. More particularly the method applies to the processing of the lidar beat signal Sb. The first steps of the method are illustrated in FIG. 7 for the case of a signal f mO d having two slopes αθ and a1.
    The method 50 according to the invention comprises a first step 501 consisting in modulating in a complex manner the beat signal Sb by the modulation frequency f mod to obtain a modulated signal S mO d ·
    FIG. 7a illustrates the variation as a function of time of the frequency of the local oscillator faith_ (t) and of the signal frequency fs (t), the average optical frequency f0 having been subtracted for greater clarity.
    FIG. 7b illustrates the two frequency components of the lidar beat signal Sb, fs-f 0L and faith_-fs. Indeed, the latter being real, it has a positive frequency component and a negative frequency component.
    FIG. 7c illustrates the variation as a function of time of the frequency of the modulated signal obtained S mO d · The actual lidar beat signal Sb is modulated in complex numerically by a frequency associated with the waveform, that is to say say foL-fO, with fO average frequency of the laser source L. We then reconstruct for the modulated signal S mO an instantaneous frequency corresponding to:
    fs-foL + (Îlo-îO) = fs-fO f L o-fs + (foL-fO) = 2f 0L - fO - fs
    Then a step 502 consists in demodulating in a complex manner the modulated signal S mod by n demodulation frequencies fdemod (i) having a single slope respectively equal to a frequency slope ai of the modulation frequency f mod , to obtain n demodulated signals S dem od (i) · Thus n complex demodulations are applied using n digital signals fdemod (i) of single slope ai.
    To take into account the periodicity of the waveform, it is necessary to return regularly to zero. The demodulation frequencies f of mod (i) are preferably periodic according to a multiple of T F0 , and preferably have a period equal to T F0 . This equality makes it possible to coincide the frequency plates (and therefore the lines, after spectral analysis) of the different waveform periods analyzed: for each frequency slope ai, the associated line will appear at the same frequency v ai and, by Consequently, the energy associated with a target signal will be concentrated in the same line after time-frequency analysis.
    Figures 7d and 7e respectively illustrate the variation as a function of time of the demodulation frequencies f mO d (0) (slope αθ) and f mO d (1) (slope a1).
    In order to readjust the different frequencies, the demodulation frequency of index i (corresponding to a slope ai) is offset by an offset time tdi depending on i, n and the modulation period T FO . Preferably, the offset time is equal to:
    tdi = i / n * T F o
    Thus for 2 slopes f mO d (0) is not offset and f mod (1) is offset by T F o / 2 (see Figure 7e).
    Figures 7f and 7g respectively illustrate the variation as a function of time of the demodulated signal S of mod (0) and S dem od (1)
    Each demodulation corresponds to the search for the signal of interest in all of the distance boxes. We then find in the demodulated signal of index i a characteristic frequency plateau v Q i. For the case of 2 slopes, S demO d (0) allows to determine v a o while S dem od (1) allows to determine v a i. The frequency v a i corresponds to the difference, measured at a time for which fs (t) -fO has a frequency slope ai, between the demodulation frequency f mO d (i) and the frequency fs (t) -fO , itself having been reconstructed using the modulation of the beat signal by the frequency foL-fO.
    Each frequency v ai corresponds to the difference, measured at a time for which fs (t) -fO has a frequency slope ai, between the demodulation frequency f mO d (i) and the frequency fs (t) -fO, itself having been reconstituted by means of the modulation of the beat signal by the frequency faith_-fO.
    In figure 7f, the widest plateau corresponds to + v a0 while the weakest plateau corresponds to -ν α ο · Indeed we adapt the demodulation function to the frequency of interest, here + v a o (speed radial of the positive target). In the same way in FIG. 7g, the widest plateau corresponds to + v a i while the weakest plateau corresponds to -v a i.
    In order to measure these characteristic frequencies, the method 50 according to the invention also includes a step 503 of determining n spectral densities SP (i) of the n demodulated signals S dem od (i) · This involves performing a time / frequency, that is to say a frequency transform of the signal S of mod (i) (t), to reveal the characteristic frequency v Q i in the form of peaks. Advantageously, it is possible to include a time window which depends on the range of analysis distance and the slope of frequency of analysis.
    FIG. 8 illustrates the spectral densities SP (0) (FIG. 8a) and SP (1) (FIG. 8b) of the spectra determined from the signals S demod (0) and S dem o d (1). The characteristic frequency sought v a i has the highest spectral density. We find a weaker peak at the opposite frequency. A negative peak at frequency zero is due to filtering of the signal for low frequencies.
    Then the method according to the invention comprises a step 504 of determining the n characteristic frequencies v ai corresponding respectively to the maximum of the n spectral densities SP (i). In fact, the frequency with the widest plateau in the signal Sdemod / i (t), which corresponds to the characteristic frequency sought, is the one with the highest spectral density.
    A second plateau of lesser duration (and therefore leading to a less intense line after spectral analysis) is also present but the corresponding frequency has a lower spectral density than that of the characteristic frequency. This signal comes from the modulations and demodulations described above on the other component of the beat signal generated by the real detection (negative frequency component if the target signal corresponds to a positive frequency or, conversely, positive frequency component if the signal target corresponds to a negative frequency)
    Finally, method 50 comprises a step 505 of determining speed information v and distance information D of the target T from said n characteristic frequencies v ai , from the formula:
    _ 2v 2a ( D ^ a, .i λ C
    For 2 frequency slopes:
    2v 2a ^ D. 2v 2a, D v = --- 'i— and v = --- ί— “” λ c “> λ c
    Note that the above formulas are valid when the laser frequency is not shifted by an acousto-optical modulator. When this is the case, with the offset frequency, the characteristic frequencies are calculated with the formula:
    2v λ
    2a, D + / mao
    The invention is of course compatible with such an offset by adapting step 505 of determining d and v from the values of the characteristic frequencies.
    Figure 7 corresponds to a target moving with a speed of 40 m / s at a distance of 12km, and the waveform of the signal f mO d includes 2 slopes αθ = 0.2 MHz / ps and a1 = -0.2 MHz / ps for an average laser frequency of 1.55 pm, or 193.41 THz. The period T F0 is equal to 532 ps.
    The characteristic frequencies detected are v a o = 35.6 MHz and v a1 = 67.6 MHz. For S m od (0), a lower peak remains at -35.6 MHz and for S mO d (1) at 67.6 MHz corresponding to the smallest plateau.
    Figure 9 is equivalent to Figure 7 but for a target located at a distance of 18 km.
    FIG. 9a illustrates the variation as a function of time of the frequency of the local oscillator faith_ (t) and of the signal frequency fs (t),
    Figure 9b illustrates the two frequency components of the lidar beat signal Sb, fs-foL and foL-fs.
    FIG. 9c illustrates the variation as a function of time of the frequency of the modulated signal obtained S mO d FIGS. 9d and 9e respectively illustrate the variation as a function of time of the demodulation frequencies f mO d (0) (slope αθ) and f mO d (1) (slope a1).
    Figures 9f and 9g respectively illustrate the variation as a function of time of the demodulated signal S d emod (0) and S of mod (1)
    It is found that the plates reappear, even at longer distance. The characteristic frequencies detected are v a o = 27.6 MHz and v a1 = 75.6 MHz. There are almost no more peaks at - 27.6 MHz and -75.6 MHz
    Thus the proposed method avoids testing all distance boxes (costly solution in calculation) and allows, by a simple modulation / demodulation operation, to find the distance from the target, as long as the laser power remains sufficient. The peaks from the backscattered signal reappear, providing a method that is no longer limited by signal processing, but only by the power of the laser.
    The calculation is carried out from the beat signal Sb (t) digitized as time goes by.
    Mathematically, the step 501 of modulation by the frequency fmod (t) = foL (t) -f0 amounts to multiplying the signal Sb (t) by a complex number C (t), also digitized, equal to:
    C = exp lt 2 ΐ π (foL ( U ) ~ fo) du = eX P 2./; / mod
    Let S mod (t) = C * Sb (t) fO: frequency of the laser without modulation foL 'frequency of the local oscillator
    Then in demodulation step 502, each demodulation amounts to multiplying the signal Smod (t) by a complex number Ci (t) defined as follows:
    C ( = exp
    2y © a ^ - ^ g ^ + floor ^ ç— ^ * T FO
    of 7.
    With i index of the slope ai, with i varaint from 0 to n-1, Tfo: period of the waveform g i (u} = floor nT,
    FO floor being the lower rounded function (for example floor (2.6) = 2 and floor (3.2) = - 4)
    Or in the end:
    ^ m od /, W = ^ W- ex P ·
    Pernod /, W = 5 ôW eX P · l
    2 M t
    2 M ((n foL ^ -fo-a ,. u- -g ^ uf + floor / modW-a, '· u - ~ sM + floor 2 z' + l
    L ^ FO
    V -1 of J.
    z '+ l
    y 1 FO ηof D 2 D
    The aiu part corresponds to the linear part, the n / 2.gi (u) .T FO / 2 part expresses the regular return to zero and the time offset, and the floor part (i + 1/2) *
    T fo / 2 corresponds to a frequency shift making it possible to bring back to zero frequency a situation for which the speed and the distance of the target are zero. This latter frequency offset compensates for a parasitic effect generated by the time offset associated with the function gi (u).
    Note that if the vertices of the waveform are rounded, these equations remain valid because this rounding is taken into account in the definition of
    Smod (t) ·
    Step 503 of obtaining the spectral densities SP (i) is typically carried out by frequency transform, taking the square of the module of the Fourier transform of the time signal S demO d / i (t):
    FFT- S b (t) .exç t day 7u - 0 k l V
    z +1
    ΊΓ from
    Preferably, step 503 of determining each spectral density comprises the sub-steps consisting in:
    -determine a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the modulation period Tfo,
    -determine each spectral density of index i SP (i) from the sum of the plurality of elementary spectral densities.
    Preferably, each elementary spectral density is determined by fast FFT Fourier transform.
    Indeed, to simplify the processing, the Fourier transforms carried out during the waveform period can be directly summed (in power). An incoherent accumulation of elementary spectral densities is therefore produced, which are then averaged.
    This operation makes it possible to carry out rapid calculations, each elementary spectral density being calculated over a short time.
    For example, for a sampling frequency of 125 MHz and a period T F o of 500 ps, performing several FFT calculations on an ot of 30ps (corresponding to 4000 points) is much more efficient than performing a calculation on the total duration of T F o (too many points).
    In addition, averaging over a certain number of FFTs during a period T F o makes it possible to improve the signal-to-noise ratio of SPi (v) without loss of information by judiciously choosing the instants at which the signal is accumulated. In fact, noise is generally limited by photon noise. The signal and noise present a chi2 statistic and, consequently, the signal to noise ratio decreases in 1 / sqrt (N) where N denotes the number of averaged spectral densities. Figures 8a and 8b correspond to an average of the spectral densities SP (0) and SP (1) carried out on several hundred FFTs (N = 864).
    The signal described by the instantaneous frequencies between the plates has a power proportional to the power of the signal concentrated in the frequency plates, but it is distributed over a number of spectral channels clearly more important. After time / frequency analysis, this signal is therefore diluted in the analysis strip and leads to:
    - at short distance to additional noise which reduces the signal to noise ratio (SNR). This decrease is not significant, however, since at close range, the SNR is high. According to one embodiment, if it is desired to avoid this reduction, a step of searching for time periods leading to a frequency plateau is added to guarantee a maximum SNR.
    - at long distance (for a lower SNR), the additional noise the effect remains lower than the detection noises (in particular the photon noise of the local oscillator), but reduce the accumulation time at the only moments when the signal is present reduces the detection noise.
    Furthermore, performing an average over a certain number of FFTs during a period T F0 makes it possible to calibrate the duration of a Fourier transform on the coherence time of the target (which depends in particular on the movements of this target) which also optimizes the signal to noise ratio.
    The spectral density calculated is preferably equal to the average of the elementary spectral densities, in order to always obtain normalized numerical values.
    From a practical point of view, the modulation / demodulation, then FFT and square of the module calculations are carried out as the beat signal is digitized, in real time. Then after a certain accumulation time, the spectral densities SP (i) are obtained by averaging the accumulated elementary spectral densities (see figure 14 below).
    The invention applies for any value of n greater than or equal to 2. FIG. 7 illustrates the method applied for n = 2. To resolve the ambiguities associated with possible aliasing, a waveform with 4 frequency ramps αθ, al, a2, a3 is preferably used. Indeed, the determination of 4 characteristic frequencies leads to a system of 4 equations, with 2 unknowns, v and d. This makes it possible to obtain redundancy and therefore to use one of the equations to resolve the ambiguities associated with possible aliasing of spectra and another as a confidence parameter. This confidence parameter can for example be the residue of the inversion between the frequencies v ai and the radial speed and distance. This inversion can be obtained by a least squares type technique, possibly iteratively weighted (Iteratively reweighted least squares - IRLS).
    As in FIG. 7 for the case of a waveform with 2 slopes, FIG. 10a illustrates the variation over time of the frequencies f O i_ (t) and f s (t), the average optical frequency fO having been subtracted for clarity. FIG. 10b illustrates the evolution over time of fs -f OL for the case with 4 slopes. We see in Figure 10b that this frequency variation over time has 4 plates corresponding to the 4 characteristic frequencies.
    As in FIG. 7 for the case of a wave form with 2 slopes, FIG. 11b illustrates the two frequency components of the lidar beat signal Sb, fs-faith_ and foL-fs, FIG. 11c illustrates the variation as a function of time the frequency of the modulated signal obtained S mO d for a waveform comprising 4 slopes. Figures 12a, 12b, 12c and 12d respectively illustrate the variation as a function of time of the demodulation frequencies f mO d (0) (slope αθ) and f mO d (1) (slope a1), f mod (2) (slope a2) and fmod (3) (slope α3), and Figures 12e, 12f, 12g and 12h respectively illustrate the variation as a function of time of the demodulated signal Sdemod (O), Sdemod (1), Sdemod (2) Ot Sdemod ( 3).
    For 4 slopes, f mO d (0) is not offset (see figure 12a), f mO d (1) is offset by Tfo / 4 (see figure 12b), f mO d (2) is offset by T FO / 2 (see figure 12c), fmod (3) is offset by% .T FO (see figure 12d).
    Figures 10 and 11 correspond to the case of a target located at 12 km, moving at 40 m / s, the frequency fmod having the following slope values (laser with optical frequency fO = 1.55 pm):
    αθ = 0.2 MHz / ps a1 = -0.2 MHz / ps a2 = 0.3 MHz / ps a3 = -0.3 MHz / ps
    By transforming in frequency space, we detect the characteristic frequencies (longest plateaus): 35.6 MHz (a 0 ), 67.6 MHz (ch), 27.6 MHz (a 2 ) and 75.6 MHz (a 3 ).
    There are also lower peaks at opposite frequencies.
    The invention also relates to a coherent lidar system illustrated in FIG. 13 and comprising:
    - a coherent source L periodically modulated in frequency,
    a device for transmitting DE of an optical signal originating from the coherent source and a device for receiving DR of a signal backscattered by a target T illuminated by the lidar,
    a photodetector D configured to generate a beat signal Sb from the interference between an optical signal called local oscillator having a local oscillator frequency f O i_ (t) and the backscattered optical signal, the local oscillator frequency faith_ (t) being made up of the sum of an average value fO and a modulation frequency f mod (t) resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period T F o, each period comprising n linear parts respectively having n slopes of frequency ai, n being greater than or equal to 2, i varying from 0 to n-1,
    -a UT processing unit configured for:
    * digitize the beat signal, * complexly modulate the beat signal Sb by the modulation frequency f mO d to obtain a modulated signal S mO d, * demodulate in a complex way the modulated signal S mO d by n demodulation frequencies fdemod (i) each having a unique slope equal to the respective frequency slope ai of the modulation frequency to obtain n demodulated signals S d emod (i), * determine n spectral densities SP (i) of the n demodulated signals, determine n characteristic frequencies v ai corresponding respectively to the maximum of the n spectral densities SP (i), determining speed information v and distance information d of the target T from said n characteristic frequencies v ai .
    Advantageously, the processing unit UT is further configured to determine, for each spectral density, a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the modulation period T F o, the spectral density SP (i) being determined from the sum of the plurality of elementary spectral densities. Preferably each elementary spectral density is determined by fast Fourier transform FFT. Preferably, the spectral density is equal to an average of the elementary spectral densities.
    Preferably, the UT processing unit comprises n channels, one channel per slope, each channel operating in parallel with the others and being configured to determine the associated frequency. Indeed, modulation and demodulation can be carried out simultaneously, thus leading to a reduced calculation cost (consisting of a single complex multiplication).
    An example of implementation of a parallel 4-way architecture (4 slopes) of the UT processing unit is illustrated in Figure 14.
    The beat signal Sb is digitized using an ADC analog / digital converter (for example a 14-bit converter, 125 MHz) then optionally filtered by a frequency filter F. The digitized and filtered signal is then distributed over the 4 tracks. Each channel operates in parallel with the others and performs the same processing chain. Only the value of the demodulation frequency fdemod (i) (and its time offset) is different from one channel to another.
    Module 2 allows you to define the amplitude and phase of the modulation and demodulation functions C and f mod (i). The product of these functions is then evaluated in module 3.
    Module 4 makes it possible to carry out the complex multiplication of the beat signal Sb digitized by the function calculated in module 3 (product of the modulation function C by the demodulation function f mod (i)).
    Module 5 performs complex Fast Fourier transforms (FFT). Module 6 calculates the norm squared of the Fourier transforms.
    The module 7 performs the sum of the spectral power densities for a time determined by the characteristics provided by the module 12 (duration, cadence, etc.). This result is transferred into a buffer 8 before being transferred via a TCP server 9 and used, in a second part of the signal processing which can be carried out more slowly. This second part, module 11 in FIG. 15, makes it possible to carry out the detection of peaks, the evaluation of the frequencies and performs the calculation of v and d taking into account all of these characteristic frequencies. This step can, for example, be carried out by the least squares technique or, by “Iteratively reweighted least squares” (IRLS), known in the literature.
    The invention also relates to a computer program product comprising code instructions making it possible to carry out the steps of the processing method according to the invention.
    In the various embodiments of the system according to the invention, the calculation modules can be arranged according to different architectures, in particular each step of the process can be implemented by a separate module or on the contrary all the steps can be grouped within a single calculation module.
    Each of the calculation modules that the system according to the invention comprises can be produced in software and / or hardware form. Each module can in particular consist of a processor and a memory. The processor can be a generic processor, a specific processor, an integrated circuit specific to an application (also known under the English name of ASIC for "Application-Specific Integrated Circuit") or a network of programmable doors in situ (also known under the English name of FPGA for "Field-Programmable Gate Array").
    权利要求:
    Claims (11)
    [1" id="c-fr-0001]
    1. Method for processing (50) a signal from a coherent lidar comprising a coherent source (L) periodically modulated in frequency,
    -a beat signal (Sb) being generated by a photodetector (D) from the interference between an optical signal called local oscillator having a local oscillator frequency (faith_ (t)) and an optical signal backscattered by a target (T) illuminated by the lidar, said beat signal being digitized,
    -the local oscillator frequency (faith_ (t)) being made up of the sum of an average value (fO) and a modulation frequency (f mO d (t)) resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period (T F o), each period comprising n linear parts respectively having n frequency slopes (ai), n being greater than or equal to 2, the method comprising the steps consisting in:
    -modulating (501) in a complex way the beat signal (Sb) by the modulation frequency (f mO d) to obtain a modulated signal (S mO d)> -demodulating (502) in a complex way the modulated signal (S mO d) by n demodulation frequencies (fdemod (i)) each having a single slope equal to the respective frequency slope (ai) of the modulation frequency (fmod), to obtain n demodulated signals (Sdemod (i)),
    -determine (503) n spectral densities (SP (i)) of the n demodulated signals (S d emo d (i)),
    -determine (504) n characteristic frequencies (ν α ,) corresponding respectively to the maximum of the n spectral densities (SP (i)),
    determining (505) speed information (v) and distance information (d) of the target (T) from said n characteristic frequencies (Vci).
    [2" id="c-fr-0002]
    2. Method according to claim 1 wherein the step of determining each spectral density comprises the sub-steps consisting in: determining a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the modulation period ( (T F o),
    -determining said spectral density (SP (i)) from the sum of the plurality of elementary spectral densities.
    [3" id="c-fr-0003]
    3. Method according to claim 2 in which each elementary spectral density is determined by fast Fourier transform (FFT), and in which the spectral density is equal to an average of the elementary spectral densities.
    [4" id="c-fr-0004]
    4. Method according to one of claims 1 or 2 wherein each demodulation frequency (fdemod (i)) is periodic according to the modulation period (T F o).
    [5" id="c-fr-0005]
    5. Method according to claim 4 in which the frequency slopes (ai) are indexed by an index i varying from 0 to n-1 and in which the each demodulation frequency (fdemod (i)) having a slope of index i is temporally offset from the modulation frequency (fmod) by an offset time (tdi) depending on i, n and the modulation period (T F0 ).
    [6" id="c-fr-0006]
    6. Method according to one of the preceding claims, in which the waveform comprises 4 slopes αθ, a1, a2, a3 with:
    α1 = - αθ and a3 = - a2
    [7" id="c-fr-0007]
    7. Coherent lidar system including:
    - a coherent source (L) periodically modulated in frequency,
    a device for transmitting (DE) an optical signal from the coherent source and a device for receiving (DR) a signal backscattered by a target (T) illuminated by the lidar,
    -a photodetector (D) configured to generate a beat signal (Sb) from the interference between an optical signal called local oscillator having a local oscillator frequency (faith_ (t)) and the backscattered optical signal, the frequency local oscillator (foL (t)) consisting of the sum of an average value (fO) and a modulation frequency (fmod (t)) resulting from the modulation of the source, the modulation frequency being periodic according to a modulation period (T F o), each period comprising n linear parts respectively having n frequency slopes (ai), n being greater than or equal to 2,
    -a processing unit (UT) configured for:
    digitize the beat signal, * complex modulation of the beat signal (Sb) by the modulation frequency (f mO d) to obtain a modulated signal (S mod ), * complex demodulation of the modulated signal (S mO d ) by n demodulation frequencies (f dem od (i)) each having a unique slope equal to the respective frequency slope (ai) of the modulation frequency to obtain n demodulated signals (S demod (i)), * determine n spectral densities (SP (i)) of the n demodulated signals, * determine n characteristic frequencies (v Q i) corresponding respectively to the maximum of the n spectral densities (SP (i)), determine speed information (v) and information distance (d) from the target (T) from said n characteristic frequencies (ν α ,).
    [8" id="c-fr-0008]
    8. Lidar system according to claim 7 in which the processing unit (UT) is further configured to determine, for each spectral density, a plurality of elementary spectral densities for a plurality of time intervals less than or equal to the period modulation (T F o). said spectral density (SP (i)) being determined from the sum of the plurality of elementary spectral densities.
    [9" id="c-fr-0009]
    9. Lidar system according to claim 8 in which each elementary spectral density is determined by fast Fourier transform (FFT), and in which the spectral density is equal to an average of the elementary spectral densities.
    [10" id="c-fr-0010]
    10. Lidar system according to one of claims 7 to 9 in which the processing unit (UT) comprises n channels, one channel per slope, each channel operating in parallel with the others and being configured to determine the associated frequency.
    [11" id="c-fr-0011]
    11. A computer program product, said computer program comprising code instructions making it possible to carry out the steps of the processing method according to any one of claims 1 to 6.
    1/13
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    优先权:
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    FR1601251|2016-08-23|
    FR1601251A|FR3055424B1|2016-08-23|2016-08-23|METHOD OF PROCESSING A SIGNAL FROM A COHERENT LIDAR AND ASSOCIATED LIDAR SYSTEM|FR1601251A| FR3055424B1|2016-08-23|2016-08-23|METHOD OF PROCESSING A SIGNAL FROM A COHERENT LIDAR AND ASSOCIATED LIDAR SYSTEM|
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    US16/325,705| US11125879B2|2016-08-23|2017-08-21|Method for processing a signal arising from coherent lidar and associated lidar system|
    PCT/EP2017/070994| WO2018036946A1|2016-08-23|2017-08-21|Method for processing a signal arising from coherent lidar and associated lidar system|
    EP17752152.3A| EP3504559B1|2016-08-23|2017-08-21|Method for processing a signal arising from coherent lidar and associated lidar system|
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    IL264821A| IL264821A|2016-08-23|2019-02-13|Method for processing a signal arising from coherent lidar and associated lidar system|
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