CN115494469A - Slow-time MIMO radar distance ambiguity suppression method based on waveform agility phase coding - Google Patents
Slow-time MIMO radar distance ambiguity suppression method based on waveform agility phase coding Download PDFInfo
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Abstract
The invention relates to a distance ambiguity suppression method for a slow-time MIMO radar, belongs to the technical field of radar signal processing, and particularly relates to a distance ambiguity suppression method for a slow-time MIMO radar based on waveform agility phase coding. And obtaining a multi-range comprehensive range-Doppler plane without range ambiguity by adopting a PAPC-DDMA waveform multi-range combined pulse-Doppler processing method based on reference signal time delay, and extracting target parameter information by a target detection algorithm. The invention better solves the distance fuzzy problem generated by the conventional DDMA waveform under the high repetition frequency application, can effectively improve the non-fuzzy speed measuring range of the DDMA waveform, and improves the detection performance of the slow-time MIMO radar on the high-speed moving target. The distance gating and target distance fuzzy suppression effects of the PAPC-DDMA waveform are verified through simulation experiments.
Description
Technical Field
The invention relates to a distance ambiguity suppression method for a slow-time MIMO radar, belongs to the technical field of radar signal processing, and particularly relates to a distance ambiguity suppression method for a slow-time MIMO radar based on waveform agility phase coding.
Background
The Multiple Input Multiple Output (MIMO) radar is a radar of a new system which is developed from a Multiple Input Multiple Output (MIMO) technology in a communication system and is combined with a digital array technology. The MIMO radar adopts the waveform diversity technology to obtain larger system freedom degree, thereby improving the detection performances of the radar such as angle measurement precision, minimum detectable speed and the like. The slow-time MIMO radar is one of the MIMO radars, doppler frequency division multiplexing (DDMA) waveforms are adopted, and slow-time initial phases of all channels are modulated, so that signals transmitted by all channels are positioned at different Doppler carrier frequencies, and orthogonal transmission is realized.
The DDMA waveform adopts a Doppler sub-band division form, and divides a Doppler plane into a plurality of channels, thereby realizing MIMO orthogonal transmission and demodulation. The DDMA waveform can be realized only by adjusting the initial phase among the pulses among the transmitting channels without changing the carrier frequency, and the DDMA waveform has good hardware compatibility and is easy to realize. However, this modulation method is at the cost of losing the unambiguous velocity measurement range of the system, and the number of MIMO channels is larger, i.e. the number of doppler sub-bands is larger, so that the doppler spectrum width occupied by each doppler sub-band is smaller, i.e. the unambiguous velocity measurement range is smaller. If the speed measurement range is improved and the influence on the radar target detection performance is reduced, the Pulse Repetition Frequency (PRF) of the system is increased by the simplest means, however, the pulse repetition Period (PRT) of the system is reduced, and the distance ambiguity of a long-distance target is generated. Therefore, it is necessary to study a distance blur suppression method of the DDMA waveform.
In the existing literature, research work is mostly carried out on the problem of speed ambiguity suppression of the DDMA waveform. Rabideau, lincoln laboratories, university of labor, ma, proposed a Frequency-perturbed (Frequency-perturbed) DDMA signal and a Phase-perturbed (Phase-perturbed) DDMA signal. The Fd-DDMA signal is subjected to pseudo-random mapping by changing the mapping relation between the Doppler sub-band and the transmitting array element, so that the signal-to-noise ratio loss at the blind speed is reduced; the Pd-DDMA signal reduces the signal-to-noise-ratio loss at the blind speed by adding random phase disturbance in the initial phase value of emission and performing matched filtering at a receiving end. Jansen, engineura semiconductor, and researchers in texas instruments, utilize redundant Doppler sub-bands (Empty Doppler sub-bands) to achieve recovery of the unambiguous velocity measurement range of DDMA waveforms. Li Fuyou of the national defense department summarizes the DDMA waveform blind speed suppression method based on multiple carrier frequencies, multiple pulse repetition frequencies and multiple pulse repetition periods.
Disclosure of Invention
The invention aims to solve the problem of range ambiguity of a DDMA waveform, and provides a method for restraining range ambiguity of a slow time MIMO radar based on waveform agility Phase coding. Meanwhile, the codes in each pulse are changed rapidly, but the carrier frequencies are the same, and pulse-Doppler processing can still be carried out, so that the speed measuring range of the DDMA waveform can be increased on the premise of keeping the unambiguous range measuring range of the system unchanged, and the influence of the speed measuring range reduction of the DDMA waveform caused by Doppler sub-band division on the radar target detection performance is improved.
The technical solution of the invention is as follows:
a method for restraining range ambiguity of a slow time MIMO radar based on waveform agility phase coding comprises the following steps:
s1, establishing a PAPC-DDMA signal model, and optimizing the established PAPC-DDMA signal model to obtain an optimized PAPC-DDMA signal model;
s2, setting target parameters in the optimized PAPC-DDMA signal model obtained in the S1 to obtain echo signals of all receiving antennas;
s3, performing multi-range combined pulse-Doppler processing on the echo signals of the receiving antennas obtained in the step S2 to obtain a multi-range comprehensive range-Doppler plane without range ambiguity corresponding to each receiving antenna;
step S4, carrying out MIMO demodulation on the multi-range comprehensive distance-Doppler plane without range ambiguity corresponding to each receiving antenna obtained in the step S3 by using a Doppler filter to obtain the multi-range comprehensive distance-Doppler plane corresponding to each demodulated MIMO receiving-transmitting channel;
and S5, performing Constant False Alarm Rate (CFAR) detection based on the multi-range comprehensive distance-Doppler plane corresponding to each MIMO receiving-transmitting channel demodulated in the step S4 to obtain unambiguous target distance information and target speed information.
In the step S1, a transceiving one-dimensional antenna array having M transmitting channels and N receiving channels is provided, each antenna in the array is an omnidirectional antenna, in the transmitting array, the M-th (M =0, …, the distance from M-1 array elements to the reference antenna is dm, in the receiving array, the nn =0, …, the distance from N-1 array elements to the reference antenna is d n The operating frequency of the radar system is f 0 At an operating wavelength of λ 0 There are K pulses in a Coherent Processing Interval (CPI), and the PRT of the radar system is T r Corresponding PRF is f r ＝1/T r The DDMA waveform divides the complete range-Doppler plane into M spectral widths of Deltaf by performing slow-time initial phase encoding on each channel sub ＝f r Doppler sub-band, slow time initial phase encoding of/M
Is a function of the transmission channel number m and the pulse number K (K =0, …, K-1), the PAPC-DDMA signal model s of the mth transmission antenna at time t m (t) is:
wherein u is pulse (t-kT r ) Baseband pulse for the kth pulse at time tThe internal modulation signal is a signal that is modulated,
α m the doppler center frequency of the baseband signal transmitted by the mth channel is:
in the step S1, optimizing the established PAPC-DDMA signal model means optimizing u in the PAPC-DDMA signal model pulse (t) obtaining a continuous phase PAPC waveform set
The specific optimization steps are as follows:
assuming that a frame of PAPC encoded signal has Q groups of different continuous phase encoded signals in its set, and the code length of each encoded signal is P bits, the Q group of phase encoded signals have their pulse modulated waveform
Expressed as:
wherein, { c qp (P =0, …, P-1) is the code sequence of the q-th set of phase-encoded signals, τ c The chip width, i.e. the time interval between two adjacent chips, thus obtaining the time t, the baseband reference signal model of a frame of PAPC encoded signal set is:
optimizing the established PAPC-DDMA signal model refers to optimizing the code sequence c qp Ensuring each coding sequence to have lower autocorrelation sidelobe peak ASP (c) q ) With low cross-correlation side-lobe peaks between code sequences
Wherein q is 1 ≠q 2 。
Firstly, a continuous phase code sequence set is initialized randomly, the number of code groups is Q, the code length is P, and the phase is theta qp The expression is as follows:
after initialization is completed, a cost function is set, the autocorrelation sidelobe peak value and the cross-correlation sidelobe peak value are used as the measurement standard of the performance of the code set, and the cost function phi (C) corresponding to the constructed code set is as follows:
wherein λ is a set weight, ASP (c) q ) For the q symbol sequence c in the code set q The calculation formula of the autocorrelation sidelobe peak value is as follows:
A(c q k) represents a code-concentrated sequence c q The mathematical expression of the autocorrelation function of (1) is:
the superscript denotes the complex conjugate,
for the qth of the code set 1 And q is 2 Code element sequence
And
the calculation formula of the cross correlation side lobe peak value is as follows:
and performing local search on the continuous phase coding sequence set, performing phase replacement on each code element in each coding sequence as a current code element in each iteration, calculating a new cost function, if the cost function corresponding to the replacement phase value is smaller than the cost function corresponding to the original phase value, taking the currently replaced phase value as the phase value of the current code element, otherwise, keeping the original phase value of the current code element unchanged, and stopping the search iteration process when the iteration times reach a preset maximum value or the cost function meets a threshold value to obtain the optimized continuous phase coding sequence set.
The optimized PAPC-DDMA transmitting signal model of the mth transmitting antenna at the time t is obtained by the following steps:
wherein, T Q ＝QT r The ratio K/Q of the number of pulses in the CPI to the number of PAPC signals in one frame is an integer;
in step S2, the set target parameters include that the distance of the target at the uniform motion point in the radar far field is R t The radial velocity of the target relative to the radar is v t Target Doppler is f t ＝2v t /λ 0 The direction of arrival of the target is phi t Then the echo signal s corresponding to the mth transmitting antenna obtained by the nth receiving antenna mn (t) is expressed as:
wherein, tau mn For echo time delay, it has the following form:
the received signal of the nth receiving antenna should be the sum of all M transmitted signals, and after down-conversion and low-pass filtering, it is expressed as:
in step S3, the method for performing multi-range combined pulse-doppler processing on the echo signals obtained by each receiving antenna includes:
step S31, using different receiving filter sets to perform matched filtering processing on the received signal to obtain matched filtering output results corresponding to different distance segments, and for the receiving filter set h corresponding to the Q (Q =0, …, Q-1) th distance segment q (t) baseband reference signal u for PAPC encoded signal set ref (t) obtained after cyclic shift of q pulses, the matched filtering output result corresponding to the q-th distance segment is expressed as:
step S32, rearranging the q-th distance segment matched filtering output result of the step S31 according to a pulse repetition period, performing slow time pulse-Doppler processing, namely windowing and zero padding along slow time, performing discrete Fourier transform to obtain distance-Doppler planes corresponding to each distance segment, and sequentially splicing the distance-Doppler planes corresponding to each distance segment to obtain a multi-distance segment comprehensive distance-Doppler plane;
matching filtering output result to the q distance segment
And (3) rearranging according to the number of pulses, and performing L-point FFT processing, wherein the result has the following form:
wherein w (k) is a slow time windowing function weight for suppressing velocity dimension sidelobes,
for the kth pulse of the q-th range segment matched filtering output result, L =0, …, L-1 represents the output of the L-th velocity channel, and the pulse-doppler processing results corresponding to the range segments are sequentially spliced to obtain a multi-range segment integrated range-doppler plane, that is:
in step S4, the method for performing MIMO demodulation on the multi-range integrated range-doppler plane without range ambiguity corresponding to each receiving antenna by using the doppler filter includes:
the MIMO demodulation of PAPC-DDMA is realized by Doppler low-pass filtering, and the Doppler frequency corresponding to the ith transmitting channel is utilizedCenter of rate alpha i To pair
And mixing, namely mixing the echoes corresponding to the ith transmitting channel to zero Doppler:
then, the cutoff frequency is used as [ - Δ f [ ] sub /2,Δf sub /2]Low pass filter pair of
Low-pass filtering is carried out to obtain a multi-range comprehensive distance-Doppler plane corresponding to the (n, i) th receiving-transmitting channel:
wherein H LP And (t, l) is the time domain response of the low-pass filter, and by analogy, a multi-range comprehensive distance-Doppler plane corresponding to each MIMO receiving-transmitting channel can be obtained, so that MIMO demodulation is realized.
Advantageous effects
The invention provides a method for restraining range ambiguity of a slow-time MIMO radar based on waveform agility phase coding. Has the following beneficial effects:
(1) In the method, the PAPC-DDMA signal model adopts an inter-pulse code type agility technology, so that the distance selectivity of the traditional DDMA waveform is obtained, and the unambiguous ranging range of the waveform is kept unchanged when the PRF of the waveform is improved.
(2) In the method, the optimized PAPC-DDMA signal model adopts a local search algorithm to improve the self-correlation and cross-correlation performance of a random phase coding sequence set.
(3) In the method, a PAPC-DDMA waveform multi-range section combined pulse-Doppler processing method based on reference signal time delay is adopted to obtain a multi-range section comprehensive range-Doppler plane without range ambiguity.
(4) The invention better solves the distance fuzzy problem generated by the conventional DDMA waveform under the high repetition frequency application, and simultaneously can effectively improve the unambiguous velocity measurement range of the DDMA waveform and improve the detection performance of the slow-time MIMO radar on the high-speed moving target. The distance gating and target distance fuzzy suppression effects of the PAPC-DDMA waveform are verified through simulation experiments.
Drawings
FIG. 1 is a schematic diagram of a PAPC-DDMA signal waveform according to the present invention;
FIG. 2 is a schematic diagram of the PAPC-DDMA signal range gating of the present invention;
FIG. 3 is a signal processing flow diagram of the method of the present invention;
FIG. 4 is a combined range-Doppler plane for multiple range bins of the PAPC-DDMA signal;
FIG. 5 is a range-Doppler plane of the LFM-DDMA signal;
FIG. 6 is a one-dimensional distance image of a speed channel where each target of the PAPC-DDMA is located;
FIG. 7 is a one-dimensional range profile of the speed channel in which each target of LFM-DDMA is located;
FIG. 8 is a velocity spectrum of a distance cell in which each target of the PAPC-DDMA is located;
FIG. 9 is a velocity spectrum of a range bin in which each target of LFM-DDMA is located.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings.
The invention provides a method for restraining range ambiguity of a slow-time MIMO radar based on waveform agility phase coding, which comprises the following steps as shown in figure 3:
s1, establishing a PAPC-DDMA signal model, and optimizing a random continuous phase coding waveform set;
the step S1 further includes the steps of:
and S11, setting a transceiving one-dimensional antenna array with M transmitting channels and N receiving channels, wherein each antenna in the array is an omnidirectional antenna. In the transmitting array, the M (M =0, …, M-1) th array element is connected to the referenceDistance of the antenna being d m . Similarly, in the receiving array, the distance from the nth (N =0, …, N-1) array element to the reference antenna is d n . Note that the definition of the array element spacing as used herein is more general and is applicable to both uniform and non-uniform arrays. Operating frequency f of radar system 0 At an operating wavelength of λ 0 . There are K pulses within one Coherent Processing Interval (CPI). PRT of radar system is T r Corresponding PRF is f r ＝1/T r 。
DDMA waveforms are separated into M spectral widths of Δ f by slow-time initial phase encoding of each channel sub ＝f r And modulating the transmission waveform of each channel into different Doppler sub-bands to realize MIMO orthogonal transmission. Slow time initial phase coding
Is a function of the transmit channel number m and the pulse number K (K =0, …, K-1). The transmit waveform corresponding to the mth transmit antenna can be expressed as:
wherein u is pulse (t) is a baseband intra-pulse modulation signal for each pulse. Let the slow-time initial phase function have the form:
the baseband signal transmitted by the mth channel will be modulated to a doppler center of alpha m Within the sub-band of (a). Let the Doppler center alpha of each sub-band m Has the following form:
to this end, the m-th channelThe transmitted baseband signal is modulated to a doppler center of alpha m Spectral width of Δ f sub In the doppler subband of (1).
Traditional DDMA waveform intra-pulse modulation uses a chirp signal, namely:
where B is the signal bandwidth, t p Is the signal pulse width. The method of the invention uses continuous phase PAPC waveform as the pulse modulation signal. Assume a frame PAPC encoded signal set
The code length of each code signal is P bits. The q-th group of the pulse modulation waveform of the phase-coded signal
Can be expressed as:
wherein c qp (P =0, …, P-1) is the code sequence of the q-th set of phase-encoded signals, τ c Is the chip width, i.e. the time interval between two adjacent chips. The baseband reference signal model for a frame of PAPC encoded signal set is thus obtained as:
substituting the PAPC pulse internal modulation waveform represented by the formula (5) into the formula (1) to obtain a PAPC-DDMA transmitting signal model corresponding to the mth transmitting antenna:
wherein T is Q ＝QT r For the frame period of the PAPC signal, the ratio K/Q of the number of pulses in the CPI to the number of the PAPC signal in one frame is selected as an integer to simplify the model. The waveform modulation scheme of the PAPC-DDMA signal is shown in fig. 1.
Step S12, optimizing the random continuous phase coding sequence set { c qp Ensuring each coding sequence to have lower autocorrelation sidelobe peak ASP (c) q ) With low cross-correlation side-lobe peaks between code sequences
Wherein q is 1 ≠q 2 . Firstly, a continuous phase coding waveform set is initialized randomly, the number of code groups is Q, the code length is P, and the phase is theta qp The expression is as follows:
after initialization is completed, a cost function is set, the autocorrelation sidelobe peak value and the cross-correlation sidelobe peak value are used as the measurement standard of the performance of the code set, and the cost function phi (C) corresponding to the constructed code set is as follows:
wherein λ is a set weight, ASP (c) q ) For the q symbol sequence c in the code set q The calculation formula of the autocorrelation sidelobe peak value is as follows:
A(c q k) denotes the code-centered sequence c q The mathematical expression of the autocorrelation function of (1) is:
the superscript denotes the complex conjugate,
for the qth of the code set 1 And q is 2 Code element sequence
And
the calculation formula of the cross correlation side lobe peak value is as follows:
and performing local search on the continuous phase coding sequence set, performing phase replacement on each code element in each coding sequence as a current code element in each iteration, calculating a new cost function, if the cost function corresponding to the replacement phase value is smaller than the cost function corresponding to the original phase value, taking the currently replaced phase value as the phase value of the current code element, otherwise, keeping the original phase value of the current code element unchanged, and stopping the search iteration process when the iteration times reach a preset maximum value or the cost function meets a threshold value to obtain the optimized continuous phase coding sequence set.
S2, initializing a system and target parameters, and setting echo time delay according to the target parameters to obtain received signals of each channel PAPC-DDMA;
assuming that the distance of a target at a uniform motion point in a radar far field is R t The radial velocity of the target relative to the radar is v t Corresponding to a target Doppler of f t ＝2v t /λ 0 The direction of arrival of the target is phi t . The echo signal s corresponding to the mth transmitting antenna obtained by the nth receiving antenna mn (t) can be expressed as:
wherein, tau mn For echo time delay, it has the following form:
further, the received signal of the nth receiving antenna should be the sum of all M transmitted signals, and after down-conversion and low-pass filtering, it can be represented as:
s3, performing multi-range combined pulse-Doppler processing on the echo signals obtained by each receiving antenna to obtain a multi-range comprehensive range-Doppler plane without range ambiguity;
the step S3 further includes the steps of:
and step S31, performing matched filtering processing on the received signals by using different receiving filter groups to obtain matched filtering output results corresponding to different distance sections. Theoretically, a PAPC encoded signal set with Q groups of different code patterns in one frame can realize unambiguous detection of up to Q range segments, and the range selectivity of the PAPC-DDMA signal is shown in fig. 2. As can be seen from FIG. 2, the corresponding receive filtering for the Q-th (Q =0, …, Q-1) range segmentGroup h q (t) baseband reference signal u, which should be a PAPC encoded signal set ref And (t) cyclically shifting the pulse by q pulses. Then the matched filter output result corresponding to the qth distance segment can be expressed as:
and step S32, rearranging the q-th distance segment matched filtering output result according to a pulse repetition period, performing slow time pulse-Doppler processing, namely windowing and zero padding along slow time, and performing discrete Fourier transform to obtain a distance-Doppler plane corresponding to each distance segment. And sequentially splicing the distance-Doppler planes corresponding to the distance sections to obtain a multi-distance section comprehensive distance-Doppler plane.
Matching filtering output result to the q distance segment
And (3) rearranging according to the number of pulses, and performing L-point FFT processing, wherein the result has the following form:
wherein w (k) is a slow time windowing function weight for suppressing velocity dimension sidelobes,
for the kth pulse of the q-th range bin matched filter output result, L =0, …, L-1 represents the output of the L-th velocity channel. Sequentially splicing the pulse-Doppler processing results corresponding to each distance segment to obtain a multi-distance segment comprehensive distance-Doppler plane, namely:
step S4, performing MIMO demodulation on the multi-range comprehensive distance-Doppler plane corresponding to each receiving antenna obtained in the step S3 by using a Doppler filter to obtain a multi-range comprehensive distance-Doppler plane corresponding to each demodulated MIMO receiving-transmitting channel;
MIMO demodulation of PAPC-DDMA can be achieved by simple doppler low pass filtering. In order to separate the response of the ith transmitting antenna on the multi-range integrated range-Doppler plane corresponding to the nth receiving antenna, the Doppler frequency center alpha corresponding to the ith transmitting channel is utilized i To pair
And mixing, namely mixing the echoes corresponding to the ith transmitting channel to zero Doppler:
then, the cutoff frequency is used as [ - Δ f [ ] sub /2,Δf sub /2]Low pass filter pair of
Low-pass filtering is carried out to obtain a multi-range comprehensive distance-Doppler plane corresponding to the (n, i) th receiving-transmitting channel:
wherein H LP (t, l) is the time domain response of the low pass filter. By analogy, a multi-range comprehensive distance-Doppler plane corresponding to each MIMO receiving-transmitting channel can be obtained, and MIMO demodulation is realized.
And S5, performing Constant False Alarm Rate (CFAR) detection based on the multi-range comprehensive range-Doppler plane to obtain target range and speed information.
An example of distance blur suppression of an object using the above method is given below.
Examples
The slow time MIMO radar system is S wave band, the antenna is a one-dimensional linear array with 6 array elements arranged in a receiving and transmitting way. The radar transmits PAPC-DDMA waveforms, wherein the intra-pulse modulated PAPC waveforms employ a 400-bit, 256-set of random continuous phase encoded waveforms. Meanwhile, compared with the target detection result of the LFM-DDMA waveform of the traditional Linear Frequency Modulated (LFM) signal, the method verifies the distance gating and target distance fuzzy suppression effect of the PAPC-DDMA waveform.
The radar waveform parameters and the radar target parameters are shown in tables 1 and 2;
TABLE 1
TABLE 2
The multi-range section synthetic range-doppler plane of the PAPC-DDMA signal after the multi-range section combined pulse-doppler processing is shown in fig. 4 (a), and the single-channel multi-range section synthetic range-doppler plane after MIMO demodulation is shown in fig. 4 (b). The results of processing using a conventional LFM-DDMA signal are shown in fig. 5. The PAPC-DDMA waveform has good range gating performance, can effectively inhibit folding echoes of each target at other range sections, and obtains a multi-range combined detection result without range ambiguity. The traditional LFM-DDMA signal generates range ambiguity, and the target is folded to other range segments, so that accurate target range information cannot be obtained.
The one-dimensional distance image of the velocity channel where each target of PAPC-DDMA and LFM-DDMA signals is located and the velocity spectrum of the located distance unit are shown in fig. 6, fig. 7, fig. 8 and fig. 9, respectively. It can be seen from fig. 6 that the PAPC-DDMA signal can realize combined detection of multiple range targets without range ambiguity, and each target of the conventional LFM-DDMA signal forms a folded echo in other range segments, which affects accurate detection of the target, as shown in fig. 7. After multi-distance segment combined pulse-Doppler processing (M =1024= 30dB), the theoretical target signal-to-noise ratio is 50dB, and the target signal-to-noise ratio is 49.7dB which is consistent with the theoretical value after the PAPC-DDMA waveform processing; after LFM-DDMA waveform processing, a target signal-to-noise ratio is obtained and 47.5dB is obtained, and compared with a theoretical value, 2.5dB is lost. It can be seen from fig. 8 and 9 that both signals can achieve effective detection of the target speed.
As can also be seen from fig. 6, although the PAPC-DDMA signal has range selectivity, each range bin object will form a higher side lobe in other range bins, and the side lobe level is constrained by the cross-correlation level between the phase codes. Under the parameters of the embodiment, the cross-correlation side lobe level of 400 bits of 256 groups of random discrete phase codes after multi-range joint pulse-Doppler processing is-35 dB.
The present invention may be embodied in other specific forms, and the foregoing description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A method for restraining range ambiguity of a slow time MIMO radar based on waveform agility phase coding is characterized by comprising the following steps:
s1, establishing a PAPC-DDMA signal model, and optimizing the established PAPC-DDMA signal model to obtain an optimized PAPC-DDMA signal model;
s2, setting target parameters in the optimized PAPC-DDMA signal model obtained in the S1 to obtain echo signals of all receiving antennas;
s3, performing multi-range combined pulse-Doppler processing on the echo signals of the receiving antennas obtained in the step S2 to obtain a multi-range comprehensive range-Doppler plane without range ambiguity corresponding to each receiving antenna;
step S4, carrying out MIMO demodulation on the multi-range comprehensive distance-Doppler plane without range ambiguity corresponding to each receiving antenna obtained in the step S3 by using a Doppler filter to obtain the multi-range comprehensive distance-Doppler plane corresponding to each demodulated MIMO receiving-transmitting channel;
and S5, performing constant false alarm rate detection based on the multi-range comprehensive distance-Doppler plane corresponding to each MIMO receiving-transmitting channel demodulated in the step S4 to obtain target distance information and target speed information without ambiguity.
2. The method for range ambiguity suppression of a slow-time MIMO radar based on waveform-agile phase-encoding as claimed in claim 1, wherein:
in step S1, a transceiving one-dimensional antenna array having M transmitting channels and N receiving channels is provided, each antenna in the array is an omnidirectional antenna, and in the transmitting array, the distance from the M-th array element to the reference antenna is d m M =0, …, M-1, the distance d from the nth element to the reference antenna in the receive array n N =0, …, N-1, and the radar system operating frequency is f 0 At an operating wavelength of λ 0 With K pulses in a coherent processing cycle, the PRT of the radar system is T r Corresponding PRF of f r ＝1/T r The DDMA waveform divides the complete range-Doppler plane into M spectral widths of Deltaf by performing slow-time initial phase encoding on each channel sub ＝f r Doppler sub-band, slow time initial phase encoding of/M
Is a function of the number m of the transmitting channel and the number K of the pulse, K =0, …, K-1, and the signal model s of the PAPC-DDMA of the mth transmitting antenna at the time t m (t) is:
wherein u is pulse (t-kT r ) The baseband intra-pulse modulated signal for the kth pulse at time t,
α m the doppler center frequency of the baseband signal transmitted by the mth channel is:
3. the method for range ambiguity suppression of a slow-time MIMO radar based on waveform-agile phase-coding as claimed in claim 2, wherein:
in the step S1, optimizing the established PAPC-DDMA signal model means optimizing u in the PAPC-DDMA signal model pulse (t) obtaining a continuous phase PAPC waveform set
(Q =0, …, Q-1), the specific optimization steps are:
assuming that a frame of PAPC encoded signal has Q groups of different continuous phase encoded signals in its set, and the code length of each encoded signal is P bits, the Q group of phase encoded signals have their pulse modulated waveform
Expressed as:
wherein, { c qp (P =0, …, P-1) is the code sequence of the q-th set of phase-encoded signals, τ c The chip width, i.e. the time interval between two adjacent chips, thus obtaining the time t, the baseband reference signal model of a frame of PAPC encoded signal set is:
firstly, a continuous phase code sequence set is initialized randomly, the number of code groups is Q, the code length is P, and the phase is theta qp The expression is as follows:
after initialization is completed, a cost function is set, the autocorrelation sidelobe peak value and the cross-correlation sidelobe peak value are used as the measurement standard of the performance of the code set, and the cost function phi (C) corresponding to the constructed code set is as follows:
wherein λ is a set weight, ASP (c) q ) For the q symbol sequence c in the code set q The autocorrelation sidelobe peak value of (a) is expressed by the mathematical expression:
A(c q k) represents a code-concentrated sequence c q The mathematical expression of the autocorrelation function of (1) is:
the superscript denotes the complex conjugate,
for the qth of the code set 1 And q th 2 Code element sequence
And
cross correlation side lobe ofPeak, the mathematical expression is:
performing local search on a continuous phase coding sequence set, performing phase replacement on each code element in each coding sequence as a current code element in each iteration, calculating a new cost function, if the cost function corresponding to a replacement phase value is smaller than the cost function corresponding to an original phase value, taking the currently replaced phase value as the phase value of the current code element, otherwise, keeping the original phase value of the current code element unchanged, and stopping the process of searching iteration when the iteration times reach a preset maximum value or the cost function meets a threshold value to obtain an optimized continuous phase coding sequence set;
the optimized PAPC-DDMA transmitting signal model of the mth transmitting antenna at the time t is obtained by the following steps:
wherein, T Q ＝QT r For the frame period of the PAPC signal, the ratio K/Q of the number of pulses in the CPI to the number of PAPC signals in one frame is an integer.
4. The method for range ambiguity suppression of the slow-time MIMO radar based on waveform-agile phase coding according to any one of claims 1-3, wherein:
in step S2, the set target parameters include that the distance of the target at the uniform motion point in the radar far field is R t The radial velocity of the target relative to the radar is v t Target Doppler is f t ＝2v t /λ 0 The direction of arrival of the target is phi t Then the echo signal s corresponding to the mth transmitting antenna obtained by the nth receiving antenna mn (t) is expressed as:
wherein, tau mn For echo time delay, it has the following form:
the received signal of the nth receiving antenna should be the sum of all M transmitted signals, and after down-conversion and low-pass filtering, it is expressed as:
5. the method for range ambiguity suppression of slow-time MIMO radar based on waveform-agile phase-encoding as claimed in claim 4, wherein:
in step S3, the method for performing multi-range combined pulse-doppler processing on the echo signals obtained by each receiving antenna includes:
step S31, using different receiving filter groups to carry out matched filtering processing on the received signals to obtain matched filters corresponding to different distance segmentsWave output result, for the receiving filter group h corresponding to the Q (Q =0, …, Q-1) th distance segment q (t) Baseband reference signal u for the PAPC encoded signal set ref (t) obtained after cyclic shift of q pulses, the matched filtering output result corresponding to the q-th distance segment is expressed as:
and S32, rearranging the q-th distance segment matched filtering output result of the step S31 according to a pulse repetition period, performing slow time pulse-Doppler processing, namely windowing and zero padding along slow time, performing discrete Fourier transform to obtain distance-Doppler planes corresponding to each distance segment, and sequentially splicing the distance-Doppler planes corresponding to each distance segment to obtain a multi-distance segment comprehensive distance-Doppler plane.
6. The method for range ambiguity suppression of a slow-time MIMO radar based on waveform-agile phase-coding as claimed in claim 5, wherein:
matching filtering output result to the q distance segment
And (3) rearranging according to the number of pulses, and performing L-point FFT processing, wherein the result has the following form:
wherein w (k) is a slow time windowing function weight for suppressing velocity dimension sidelobes,
matching the kth pulse of the filter output result for the qth distance segment, wherein L =0, … and L-1 represents the output of the ith speed channel, and sequentially splicing the pulse-Doppler processing results corresponding to the distance segments to obtain the multi-distance-segment comprehensive distance-multiThe plerian plane, i.e.:
7. the method for suppressing range ambiguity of slow-time MIMO radar based on waveform agile phase encoding as claimed in claim 1, wherein:
in step S4, the method for performing MIMO demodulation on the multi-range integrated range-doppler plane without range ambiguity corresponding to each receiving antenna by using the doppler filter includes:
the MIMO demodulation of PAPC-DDMA is realized by Doppler low-pass filtering, and the Doppler frequency center alpha corresponding to the ith transmitting channel is utilized i To pair
And mixing, namely mixing the echoes corresponding to the ith transmitting channel to zero Doppler:
using a cut-off frequency of [ - Δ f sub /2,Δf sub /2]Low pass filter pair of
Low-pass filtering is carried out to obtain a multi-range comprehensive distance-Doppler plane corresponding to the (n, i) th receiving-transmitting channel:
wherein H LP And (t, l) is the time domain response of the low-pass filter, and by analogy, a multi-range comprehensive distance-Doppler plane corresponding to each MIMO receiving-transmitting channel can be obtained, so that MIMO demodulation is realized.
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