CN112034483B - Multi-target distance-speed decoupling method based on coherent detection correlation imaging technology - Google Patents

Multi-target distance-speed decoupling method based on coherent detection correlation imaging technology Download PDF

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CN112034483B
CN112034483B CN202010887539.9A CN202010887539A CN112034483B CN 112034483 B CN112034483 B CN 112034483B CN 202010887539 A CN202010887539 A CN 202010887539A CN 112034483 B CN112034483 B CN 112034483B
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CN112034483A (en
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韩申生
潘龙
龚文林
邓陈进
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Shanghai Institute of Optics and Fine Mechanics of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/08—Systems determining position data of a target for measuring distance only
    • G01S17/10—Systems determining position data of a target for measuring distance only using transmission of interrupted, pulse-modulated waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/50—Systems of measurement based on relative movement of target
    • G01S17/58—Velocity or trajectory determination systems; Sense-of-movement determination systems

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Abstract

The invention discloses a multi-target distance-speed decoupling method based on coherent detection correlated imaging technology, which comprises the steps of modulating the amplitude or the phase of signal light by using an amplitude modulation or phase modulation mode, transmitting the signal light to a target through a traditional correlated imaging device, mixing the signal light containing target information with local oscillator light by using a coherent receiving mode, collecting difference frequency signals measured for multiple times by a computer, extracting frequency spectrums containing the distance and the speed information of the target to be measured by using a Fourier transform method, reconstructing a target image by using a correlated imaging algorithm according to the moving characteristics of the target frequency spectrums, and finally combining the frequency spectrum characteristics and the image characteristics of the target to obtain the distance information and the speed information of the target. Therefore, the information extraction and the target distinguishing of the speed, the distance and the two-dimensional image of the frequency spectrum overlapping multiple targets are realized.

Description

Multi-target distance-speed decoupling method based on coherent detection correlation imaging technology
Technical Field
The invention relates to the field of coherent detection-based correlation imaging, in particular to a multi-target distance-speed decoupling method based on a coherent detection correlation imaging technology.
Background
With the development of remote sensing detection and investigation monitoring technology, a remote imaging technology integrating high resolution, all-time, strong environmental applicability and multi-dimensional information acquisition has become the mainstream development direction. The development of national defense and civil technologies puts new requirements on various performances including real-time property, accuracy and multi-dimensionality of information, and is an opportunity and a challenge for a remote sensing detection technology. The development of the traditional remote sensing technology is difficult to adapt to the information requirement of modernization. Traditional non-scanning laser radar passes through the mode of floodlight illumination, utilizes the area array detector to realize every point information acquisition of target, in practical application, probably has the relative motion that is difficult to ignore between target and the platform, will lead to gathering the degree of difficulty aggravation of this information, even unable collection. Conventional scanning lidar generally implements zonal or spot scanning of a target by means of a point detector or a line detector. The scanning laser radar can realize high-precision and quick scanning, but the scanning laser radar has large data volume and complex system structure, often needs complex post-processing algorithm and also puts high requirements on the system. The intensity correlation imaging technology is a novel staring imaging technology, and has the capabilities of super-resolution, high sensitivity, high image acquisition efficiency and improvement of the influence of atmospheric interference on the imaging quality to a certain extent. As with conventional lidar technology, early intensity-correlated imaging lidar employed narrow pulses and high monopulse energies to achieve these requirements for high range resolution and long detection distances. However, in practice, there is an irreconcilable conflict between narrow pulses and high single pulse energies due to the power limitations of the narrow pulse laser itself. In general, a long-range signal has the following characteristics: very low signal energy and peak power. In the coherent detection technology, in order to realize weak signal detection and have time resolution capability, a pulse compression method is adopted for realization. The specific method comprises the following steps: the amplitude of the laser is linearly modulated and divided into two paths, one path is local oscillation light which occupies main energy and is left at the local, the other path is signal light which is emitted to a remote place, and the local oscillation light and the received signal light generate interference in a balanced detector and output an intermediate frequency electric signal. Inspired by this, a pulse compression coherent detection laser correlation imaging technology based on chirp amplitude modulation is proposed. Since the chirped amplitude modulation coherent detection technology is based on frequency measurement, the mutual motion between the platform and the moving object is reflected on the Doppler frequency, and therefore the correlated imaging technology based on chirped amplitude modulation coherent detection also has the capability of speed measurement. Therefore, the chirp amplitude modulation coherent detection correlation imaging technology has four-dimensional information acquisition capability including three-dimensional space information and speed information of the target.
In a typical scenario, there is relative motion between the target and the platform. At this time, the laser radar based on the conventional pulse compression system has range-doppler velocity coupling, which results in the generation of a ranging error, and the ranging error is proportional to the doppler frequency. Although research algorithms exist that try to eliminate this error, it is still not very good. Especially for multi-objective scenarios, these algorithms basically fail.
Disclosure of Invention
The invention aims to eliminate the distance-Doppler coupling phenomenon in the traditional laser radar ranging and speed measurement by using the chirp amplitude modulation coherent detection correlation imaging technology so as to realize multi-target multi-dimensional information extraction including multi-target imaging, ranging and speed measurement.
The basic idea of the invention is: the chirp amplitude modulation coherent detection technology is combined with the correlation imaging technology, and the speed information of the target is measured while the target is imaged in three dimensions. The speckle pattern is loaded on a Digital Micromirror Device (DMD) or a liquid crystal Spatial Light Modulator (SLM), and the complexity of the system is reduced by utilizing the characteristic of single-arm correlation imaging. The chirp signal is modulated onto the laser through the electro-optical modulator, so that the signal light has time domain amplitude chirp within a pulse duration, the signal light is spatially modulated through the DMD or SLM, the signal light modulated in a space-time two-dimensional mode is transmitted to a target and then received and returned, the signal light and the local oscillation light are introduced into a coherent receiver, and the receiver outputs a low-frequency IQ signal. After passing through the filtering system, the IQ signal is collected by the industrial personal computer and further processed. The IQ signals of single measurement are added in complex number, and then Fourier transform is carried out on the signals to extract frequency spectrum. And (3) correlating the intensity signal at the same spectral peak position obtained by multiple measurements by utilizing the properties of correlated imaging with a known reference signal to obtain a target image at the spectral peak position. And comparing the correlation images at different spectral peak positions to determine which target the different spectral peaks respectively come from. If one target only contributes one spectral peak, the spectral peak is the distance spectrum of the target; if a target contributes two spectrum peaks, the low spectrum position is the doppler velocity spectrum position of the target, and the high spectrum position is the spectrum position of the target where the distance spectrum and the velocity spectrum are superposed. And calculating to obtain corresponding distance spectrum values by using the spectrum values of the velocity spectrum positions and the spectrum values of the distance-velocity coupling. And finally, respectively calculating the distance and speed information of the corresponding target by using a corresponding formula of the distance spectrum and the distance and a corresponding formula of the speed spectrum and the speed.
The technical solution of the invention is as follows:
step 1, step 1) building a light path: the system comprises a continuous narrow-linewidth laser, an electro-optic modulator, a chirp signal source, an optical fiber beam splitter, a single-frequency optical fiber amplifier, a collimator, a Digital Micromirror Device (DMD) or a liquid crystal spatial light modulator (SML), an optical transmitting system, a target, a receiving device, a receiving optical fiber, an optical coherent receiver, an industrial personal computer and a filtering system; the method comprises the following specific steps:
the output light of the continuous narrow linewidth laser is modulated by the electro-optic modulator to have a time domain chirp waveform, and is divided into two paths by the optical fiber beam splitter, one path of signal light is amplified by the single-frequency optical fiber amplifier, collimated and output to a free space, and irradiated on the DMD or SLM to complete spatial modulation; the optical emission system images the DMD surface speckle pattern to a target surface, and signal light reflected by the target is injected into an optical coherent receiver through a receiving optical fiber after passing through a receiving device; the other path of light is injected into the optical coherent receiver as local oscillation light; the optical coherent receiver outputs IQ signals, and the IQ signals are collected by an industrial personal computer after passing through a filtering system; the industrial personal computer simultaneously controls the chirp signal source and the DMD or SML and ensures the time sequence synchronization of the two paths of signals; loading a plurality of pre-generated speckle patterns A onto the DMD or the SLM by the industrial personal computer;
step 2) setting chirp signal parameters required by measurement, wherein the parameters specifically comprise: pulse duration T and oscillation starting frequency f of chirp signal0Modulation width B, etc. The chirp-modulated signal is made to have the following form:
Figure BDA0002656004960000031
wherein I0Is the average light intensity reaching the electro-optic modulation, k is the modulation rate and k is B/T.
Step 3) opening the continuous narrow linewidth laser and the industrial personal computer, and controlling the chirp signal source and the DMD or SML to work;
and 4) processing the acquired signals by the industrial personal computer, wherein the method specifically comprises the following steps:
step 4.1) carrying out complex addition on the IQ two-path signals to obtain a complex signal SiThe formula is as follows:
Si＝Ii+jQi，
wherein, IiFor the I-th measured signal, QiThe signal is the Q path signal of the ith measurement;
a complex signal SiFourier transform reading is carried out and the frequency spectrum position f corresponding to the ith measurement is storedi nAnd intensity Yi n：
Figure BDA0002656004960000032
Wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002656004960000033
to represent the velocity spectrum corresponding to the o-th object, Ri,oThe position of the o-th target at the i-th measurement, c represents the speed of light, ALORepresents the local oscillator light amplitude, | At,i,o(xt)|2Representing the o-th object plane xtSignal light amplitude at the ith measurement;
if there are N targets in the field of view, where a is stationary, then the total number of spectra is N, and N is 2N-a;
step 4.2) aligning the frequency spectrum position, which specifically comprises the following steps:
the frequency spectrum obtained by the first measurement is marked as a reference frequency spectrum, the reference frequency spectrum is marked as 1,2, …, p, … and N according to the frequency spectrum positions from small to large, and the frequency spectrum size is marked as { f1,f2,…,fp,…,fNAnd recording the corresponding spectral intensity { Y }1 1,Y1 2,…,Y1 p,…,Y1 N}; then, the frequency spectrum of the second measurement is sequentially 1,2, …, p, … and N according to the frequency spectrum positions from small to large, and the corresponding frequency spectrum intensity { Y is recorded2 1,Y2 2,…,Y2 p,…,Y2 N}; finishing the spectrum alignment processing of IQ signals acquired by all M times of measurement acquisition to obtain the spectrum intensity
Figure BDA0002656004960000041
And 5) performing correlation operation on the Y signal obtained in the step 4 and the reference speckle A to obtain a target image, and determining a corresponding target velocity spectrum and a distance-velocity coupling spectrum according to the frequency spectrum position of the image. The method comprises the following specific steps:
for spectral position p, aligning the spectrum to obtain the spectral strength of M measurements at p
Figure BDA0002656004960000042
Performing correlation imaging operation with the reference speckle A to obtain a reconstructed image G at the position ppThe formula is as follows:
Gp＝<δAδYi p>＝<(A-<A>)(Yi p-<Yi p>)>
comparing reconstructed images G at all N spectral targets1,G2,…,Gp,…,GNDetermining the target number if the target number is the same;
and 6) obtaining the distance spectrum and the velocity spectrum size of the target according to the velocity spectrum and the distance-velocity spectrum position belonging to the same target image, and calculating the distance and the velocity of the target according to the distance spectrum and the velocity spectrum calculation corresponding distance and velocity formulas. The method comprises the following specific steps:
step 6.1) for the same spectral position of the reconstructed image, the small spectral position is the velocity spectrum, the large spectral position is the distance-velocity coupled spectrum, and f is assumed1，fpWhere the reconstructed image is the same and O, then f1Velocity spectrum f of OvO，fpFor the distance-velocity coupled spectrum, the distance spectrum of the object O is fRO＝f1-fp(ii) a In addition, for stationary objects, only the distance spectrum exists.
Step 6.2) calculates the distance and velocity corresponding to the distance spectrum and velocity spectrum obtained in the target step 6.1), and the formula is as follows:
Figure BDA0002656004960000043
compared with the prior art, the invention has the technical effects that:
1) by combining the pulse compression coherent detection technology and the correlation imaging technology, the contradiction between single pulse energy and ranging resolution is solved, and simultaneously, the distance and speed information of the target is recorded by utilizing the characteristic that the target can be imaged at different frequency spectrum positions. And finally, comparing the targets to obtain the distance information and the speed information of the targets, and realizing the distance-speed decoupling of the targets. This approach works for either a single target or multiple targets.
2) Corresponding parameters can be set for the high-speed or low-speed moving target so as to realize measurement in a large speed range.
3) The application of the single-arm correlation imaging system enables the system structure to be simpler, and the coherent detection mode is adopted to enable the system to have higher sensitivity.
Drawings
FIG. 1 is a diagram of an apparatus for a coherent detection correlation imaging system based on pulse compression
The figures are labeled as follows:
1-narrow linewidth optical fiber laser 2-electro-optic modulator 3-chirp signal source 4-optical fiber beam splitter 5-single-frequency optical fiber amplifier 6-collimator 7-Digital Micromirror Device (DMD) or liquid crystal spatial light modulator (SML) 8-optical transmitting system 9 target 10-receiving device 11-receiving optical fiber 12-optical coherent receiver 13-filtering system 14-industrial personal computer
FIG. 2 is a flow chart of a multi-target distance-speed decoupling method based on coherent detection correlation imaging technology
FIG. 3 first pulse measurement spectrogram
FIG. 4 is a diagram of the correlation imaging results corresponding to the measured spectral position of the first pulse
FIG. 5 Overall imaging distance-Gray level results plot
Detailed Description
The invention will be further illustrated with reference to the following examples and figures, without limiting the scope of the invention thereto
Referring to fig. 1, fig. 1 is a device diagram of a pulse compression coherent detection correlation imaging system, according to which a MATLAB platform is used to complete simulation verification of the method of the present invention. The specific implementation mode is as follows: a random bernoulli speckle pattern a with duty cycle of 0.5 with a size of 128 x 128 was selected and loaded on the DMD. According to the requirements of distance measurement and speed measurement, proper modulation bandwidth and pulse duration are set, the distances of the targets H, I and T are 1000m, 1004m and 1008m respectively in the implementation, the movement speeds are 2m/s, 3m/s and 0m/s respectively, therefore, the selected chirp modulation bandwidth is 500MHz, the modulation duration is 500 mus, and the modulation repetition frequency is 1 KHz.
After all parameters are set, the continuous narrow linewidth laser emits light, and the light amplitude is modulated by the electro-optic modulator to have a time-domain chirp waveform. Dividing the modulated light into two paths, wherein one path of the modulated light is used as signal light and is output to a free space after being amplified and collimated by a single-frequency optical fiber amplifier; and the other path is injected into the optical coherent receiver as local oscillation light. The signal light output to the free space after being collimated by the collimator is irradiated on the DMD, and the signal light on the DMD completes spatial modulation. The correlated imaging emission system images the DMD surface speckle pattern onto the target surface. The return optical signal after passing through the target is received by the bare fiber after passing through the optical receiving device and is injected into the optical receiver. In an optical coherent receiver, signal light and local oscillator light complete optical bridging and then complete double-balance detection. The four-way bridge output has the form:
Figure BDA0002656004960000061
where s is the signal light and l is the local oscillator light. In double balanced probing, I1And I2、Q1And Q2Are injected into two balanced detectors for interference. The balance detector is used for outputting two paths of differential signals. Thus, the output IQ of the two balanced detectors is:
Figure BDA0002656004960000062
and finally, acquiring IQ two-path signals after passing through the filtering system by an industrial personal computer. This completes a single measurement process. It should be noted that the DMD speckle pattern remains the same during a single acquisition, and differs from measurement to measurement.
After 10000 acquisitions in this implementation are completed, the data processing process begins. Firstly, carrying out complex addition, specifically, measuring the ith measurement data I of the I pathiIth measurement data Q of Q pathiComplex addition:
Si＝Ii+jQi(4)
and for each time of complex signal SiFourier transform to obtain spectrogram
Figure BDA0002656004960000063
The next process is spectral alignment. Taking the spectrum in the spectrum obtained by the first measurement as the reference spectrum, finding the spectrum peaks therein, as shown in fig. 3, where there are 5 spectrum peaks P1, P2, P3, P4 and P5, and the intensities of these 5 spectrum peaks are taken as the Y signal of the first measurement. Comparing the frequency spectrum obtained in the second time with the frequency spectrum measured in the first time, finding that the frequency spectrum peak measured in the second time also has 5 frequency spectrum peaks, and the position of the frequency spectrum can not see the change with the first time, and at this time, considering that the frequency spectrum peak is the same as the position of the first time, and only the intensity is different, and regarding the intensities of the five frequency spectrum peaks as Y signals measured in the second time. Similarly, the Y signal of the third, fourth, … …, 10000 th measurement can be obtained. It should be noted that although the peak positions of the spectrograms of the two adjacent measurements do not show any significant change, the first spectrogram and the last spectrogram still have significant differences in the 10000 measurements, but here, the continuity is only provided according to the target motion, and the spectral positions are considered to be unchanged during the calculation. Most importantly: in the calculation, 10000 intensities of a spectrum peak position come from a target, and the 10000 intensities are used as a set of Y signals for intensity correlation imaging processingTo reconstruct the original target image. Since there are 5 peaks in the sample, there are 5 groups Y, and they are respectively denoted as Y1，Y2，Y3，Y4And Y5. By using the five groups of Y and the reference matrix A to perform correlation operation, 5 groups of images can be obtained.
According to the correlation imaging formula, the ith group of images is:
Gi＝<δAδYi>＝<(A-<A>)(Yi-<Yi>)> (5)
wherein, the values of i are 1,2,3,4, and 5, which are arranged in sequence from small to large according to the frequency spectrum position in this example. The imaging result is shown in fig. 4.
The similarity of these 5 groups of images was compared, and G was found to be among them1And G4Are likewise "H", G2And G5Likewise, is "I". Then Y can be determined1Velocity spectrum with a spectral position "H", Y4Distance-coupled spectra with "H" at location. Similarly, Y can be determined2Velocity spectrum with "I" at spectral position, Y5Distance-coupled spectra with "I" at location. Due to Y3The corresponding image "T" has only one spectrum, so the target is a stationary target, and the location of the spectrum is the distance spectrum of "T". Subtracting the distance spectrum from the distance-velocity spectrum of "H" can obtain the distance spectrum of "H", and similarly, the distance spectrum of "I".
And finally, calculating the distance R and the speed v of the corresponding target according to the frequency spectrum calculation relationship respectively corresponding to the speed and the distance:
Figure BDA0002656004960000071
the velocity spectrum for "H" is 2.58MHz, the distance-velocity spectrum is 9.248MHz, "I" corresponds to 3.872MHz, the distance-velocity spectrum is 10.56MHz, and "T" corresponds to 6.72MHz according to the simulation in this example. The distance of H is 1002m and the speed is 2.0m/s according to the formula (6); the distance of "I" is 1003.2m, and the speed is 3.0 m/s; the distance of "T" is 1008 m. Compared with the original parameters set by simulation in the example, the distance can be accurately measured for the static target T. This is because the distance resolution Δ R/2B is 0.3m and the velocity resolution Δ v is λ/2T is 1.5mm/s in this example. The left and right deviations from the distance for "T" should also be within this range and therefore can be considered as accurate recovery. But for moving objects "H" and "I", the velocity can be considered as an accurate recovery with a slight error in distance, but the overall can also be considered as an accurate recovery. Fig. 5 is a gray scale image, which is a target distance restored from initial distance information. The invention can simultaneously give the distance information and the speed information of a plurality of targets to be measured, has imaging capability and avoids the problem that the target information cannot be distinguished due to spectrum aliasing.

Claims (1)

1. A multi-target distance-speed decoupling method based on coherent detection correlation imaging is characterized by comprising the following steps:
step 1), building a light path: the system comprises a continuous narrow-linewidth laser, an electro-optic modulator, a chirp signal source, an optical fiber beam splitter, a single-frequency optical fiber amplifier, a collimator, a Digital Micromirror Device (DMD) or a liquid crystal spatial light modulator (SML), an optical transmitting system, a target, a receiving device, a receiving optical fiber, an optical coherent receiver, an industrial personal computer and a filtering system; the method comprises the following specific steps:
the output light of the continuous narrow linewidth laser is modulated by the electro-optic modulator to have a time domain chirp waveform, and is divided into two paths by the optical fiber beam splitter, one path of signal light is amplified by the single-frequency optical fiber amplifier, collimated and output to a free space, and irradiated on the DMD or SLM to complete spatial modulation; the optical emission system images the DMD surface speckle pattern to a target surface, and signal light reflected by the target is injected into an optical coherent receiver through a receiving optical fiber after passing through a receiving device; the other path of light is injected into the optical coherent receiver as local oscillation light; the optical coherent receiver outputs IQ signals, and the IQ signals are collected by an industrial personal computer after passing through a filtering system; the industrial personal computer simultaneously controls the chirp signal source and the DMD or SML and ensures the time sequence synchronization of the two paths of signals; loading a plurality of pre-generated speckle patterns A onto the DMD or the SLM by the industrial personal computer;
step 2) setting parameters of a chirp signal source, comprising the following steps: pulse duration T and oscillation starting frequency f of chirp signal0A modulation width B, the chirp modulated signal having the form:
Figure FDA0002656004950000011
wherein, I0Is the average light intensity reaching the electro-optic modulator, k is the modulation rate, and k is B/T;
step 3), opening the continuous narrow linewidth laser and the industrial personal computer, and controlling the chirp signal source and the DMD or SML to work;
and 4) processing the acquired signals by the industrial personal computer, wherein the method specifically comprises the following steps:
step 4.1) carrying out complex addition on the IQ two-path signals to obtain a complex signal SiThe formula is as follows:
Si＝Ii+jQi，
wherein, IiFor the I-th measured signal, QiThe signal is the Q path signal of the ith measurement;
a complex signal SiFourier transform reading is carried out and the frequency spectrum position f corresponding to the ith measurement is storedi nAnd intensity Yi n：
Figure FDA0002656004950000012
Wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0002656004950000013
to represent the velocity spectrum corresponding to the o-th object, Ri,oThe position of the o-th target at the i-th measurement, c represents the speed of light, ALORepresents the local oscillator light amplitude, | At,i,o(xt)|2Representing the o-th object plane xtSignal light amplitude at the ith measurement;
if there are N targets in the field of view, where a is stationary, then the total number of spectra is N, and N is 2N-a;
step 4.2) aligning the frequency spectrum position, which specifically comprises the following steps:
the frequency spectrum obtained by the first measurement is marked as a reference frequency spectrum, the reference frequency spectrum is marked as 1,2, …, p, … and N according to the frequency spectrum positions from small to large, and the frequency spectrum size is marked as { f1,f2,…,fp,…,fNAnd recording the corresponding spectral intensity { Y }1 1,Y1 2,…,Y1 p,…,Y1 N}; then, the frequency spectrum of the second measurement is sequentially 1,2, …, p, … and N according to the frequency spectrum positions from small to large, and the corresponding frequency spectrum intensity is recorded
Figure FDA0002656004950000021
Finishing the spectrum alignment processing of IQ signals acquired by all M times of measurement acquisition to obtain the spectrum intensity
Figure FDA0002656004950000022
Step 5) associated imaging operation is carried out, the number of targets and the contribution positions of the targets to the frequency spectrum are distinguished, and the method specifically comprises the following steps: for spectral position p, aligning the spectrum to obtain the spectral strength of M measurements at p
Figure FDA0002656004950000023
Performing correlation imaging operation on the reference speckle A to obtain a reconstructed image G at the position ppThe formula is as follows:
Gp＝<δAδYi p>＝<(A-<A>)(Yi p-<Yi p>)>
comparing reconstructed images G at all N spectral targets1,G2,…,Gp,…,GNDetermining the target number if the target number is the same;
step 6) distinguishing a velocity spectrum and a distance-Doppler velocity coupling spectrum of the target, and calculating the distance and the velocity of the target, wherein the steps are as follows:
step 61) for the same spectral position of the reconstructed image, velocity spectrum at the small spectral position and distance-velocity coupled spectrum at the large spectral position, assuming f1，fpWhere the reconstructed image is the same and O, then f1Velocity spectrum of O
Figure FDA0002656004950000024
fpFor the distance-velocity coupled spectrum, the distance spectrum of the object O is
Figure FDA0002656004950000025
In addition, for stationary objects, only the distance spectrum exists.
Step 6.2) calculates the distance and velocity corresponding to the distance spectrum and velocity spectrum obtained in the target step 6.1), and the formula is as follows:
Figure FDA0002656004950000031
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