CN115494469A - A Range Ambiguity Suppression Method for Slow Time MIMO Radar Based on Waveform Agile Phase Coding - Google Patents

A Range Ambiguity Suppression Method for Slow Time MIMO Radar Based on Waveform Agile Phase Coding Download PDF

Info

Publication number
CN115494469A
CN115494469A CN202211066968.5A CN202211066968A CN115494469A CN 115494469 A CN115494469 A CN 115494469A CN 202211066968 A CN202211066968 A CN 202211066968A CN 115494469 A CN115494469 A CN 115494469A
Authority
CN
China
Prior art keywords
range
doppler
distance
papc
ddma
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202211066968.5A
Other languages
Chinese (zh)
Other versions
CN115494469B (en
Inventor
宋媛媛
杨发伟
张凯翔
李元帅
刘海波
王剑峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Cec Jinjiang Info Industrial Co ltd
Beijing Institute of Technology BIT
Original Assignee
Cec Jinjiang Info Industrial Co ltd
Beijing Institute of Technology BIT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Cec Jinjiang Info Industrial Co ltd, Beijing Institute of Technology BIT filed Critical Cec Jinjiang Info Industrial Co ltd
Priority to CN202211066968.5A priority Critical patent/CN115494469B/en
Publication of CN115494469A publication Critical patent/CN115494469A/en
Application granted granted Critical
Publication of CN115494469B publication Critical patent/CN115494469B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Radar Systems Or Details Thereof (AREA)

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

一种基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制 方法Range ambiguity suppression for slow-time MIMO radar based on waveform-agile phase coding method

技术领域technical field

本发明涉及慢时间MIMO雷达距离模糊抑制方法，属于雷达信号处理技术领域，特别涉及一种基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制方法。The invention relates to a range ambiguity suppression method for a slow-time MIMO radar, belonging to the technical field of radar signal processing, in particular to a range ambiguity suppression method for a slow-time MIMO radar based on waveform agility phase coding.

背景技术Background technique

多输入多输出(MIMO)雷达是从通信系统中的多输入多输出技术发展而来，并与数字阵列技术相结合而形成的新体制雷达。MIMO雷达采用波形分集技术来获得更大的系统自由度，从而提高雷达的测角精度、最小可检测速度等探测性能。慢时间MIMO雷达作为MIMO雷达的一种，采用多普勒频分复用(DDMA)波形，通过对各通道的慢时间初相进行调制，使得各通道发射信号位于不同的多普勒载频，从而实现正交发射。Multiple-input multiple-output (MIMO) radar is a new radar system developed from multiple-input multiple-output technology in communication systems and combined with digital array technology. MIMO radar uses waveform diversity technology to obtain greater system freedom, thereby improving the detection performance of the radar such as angle measurement accuracy and minimum detectable speed. As a kind of MIMO radar, slow-time MIMO radar adopts Doppler frequency division multiplexing (DDMA) waveform, and modulates the slow-time initial phase of each channel so that the transmitted signals of each channel are located at different Doppler carrier frequencies. Orthogonal emission is thus achieved.

DDMA波形采用多普勒子带划分的形式，将多普勒平面分为若干通道，从而实现MIMO正交发射与解调。DDMA波形仅通过调整各发射通道之间的脉间初相即可实现，不需要改变载频，硬件兼容性好，易于实现。然而，这一调制方式以损失系统的无模糊测速范围为代价，MIMO通道数越多，即多普勒子带数越大，从而导致每个多普勒子带所占据的多普勒谱宽越小，即无模糊测速范围越小。若要改善测速范围降低对雷达目标探测性能的影响，最简单的手段即提高系统的脉冲重复频率(PRF)，然而这会导致系统的脉冲重复周期(PRT)降低，远距离的目标将会产生距离模糊。因此，有必要研究DDMA波形的距离模糊抑制方法。The DDMA waveform adopts the form of Doppler sub-band division, and divides the Doppler plane into several channels, so as to realize MIMO orthogonal transmission and demodulation. The DDMA waveform can be realized only by adjusting the initial pulse-to-pulse phase between each transmitting channel, without changing the carrier frequency, good hardware compatibility, and easy to implement. However, this modulation method is at the cost of losing the unambiguous speed measurement range of the system. The more MIMO channels, that is, the larger the number of Doppler sub-bands, resulting in the Doppler spectral width occupied by each Doppler sub-band The smaller it is, the smaller the range of speed measurement without ambiguity. In order to improve the impact of the reduction of the speed measurement range on the radar target detection performance, the simplest means is to increase the pulse repetition frequency (PRF) of the system. The distance is blurred. Therefore, it is necessary to study the range ambiguity suppression method of DDMA waveform.

现有文献中大多针对DDMA波形的速度模糊抑制问题开展研究工作。麻省理工大学林肯实验室的Rabideau提出了频率扰动(Frequency-dithered)DDMA信号与相位扰动(Phase-dithered)DDMA信号。Fd-DDMA信号通过改变多普勒子带与发射阵元的映射关系，使其为伪随机映射，降低盲速处的信杂噪比损失；Pd-DDMA信号通过在发射初相值中增加随机相位扰动，并在接收端进行匹配滤波，降低盲速处的信杂噪比损失。恩智浦半导体公司的Jansen，以及德州仪器的研究人员利用冗余多普勒子带(Empty Doppler sub-band)，实现DDMA波形无模糊测速范围的恢复。国防科大的李福友总结了基于多载频、多脉冲重复频率、多脉冲重复周期的DDMA波形盲速抑制方法。In the existing literature, most of the research work is carried out on the problem of speed ambiguity suppression of DDMA waveform. Rabideau of Lincoln Laboratory of Massachusetts Institute of Technology proposed Frequency-dithered DDMA signal and Phase-dithered DDMA signal. The Fd-DDMA signal changes the mapping relationship between the Doppler subband and the transmitting array element to make it a pseudo-random mapping, which reduces the SNR loss at the blind speed; the Pd-DDMA signal increases the random Phase perturbation, and matched filtering at the receiving end to reduce the loss of signal-to-noise ratio at the blind speed. Jansen of NXP Semiconductors, and researchers from Texas Instruments used redundant Doppler sub-bands (Empty Doppler sub-band) to realize the recovery of DDMA waveforms without ambiguity in the speed measurement range. Li Fuyou from National University of Defense Technology summarized the blind speed suppression method of DDMA waveform based on multi-carrier frequency, multi-pulse repetition frequency and multi-pulse repetition period.

发明内容Contents of the invention

本发明的目的是为了解决DDMA波形的距离模糊问题，提供了一种基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制方法，该方法通过采取脉间捷变相位编码(Pulse-agile Phase-coded，PAPC)技术，可以获得距离选通性能，使得当提高波形的脉冲重复频率时，保持波形的无模糊测距范围不变。同时，各脉冲脉内编码捷变，但载频相同，仍然可以进行脉冲-多普勒处理，因此可以在保持系统无模糊测距范围不变的前提下，提高DDMA波形的测速范围，改善DDMA波形因多普勒子带划分造成的测速范围降低对雷达目标探测性能的影响。The purpose of the present invention is in order to solve the distance ambiguity problem of DDMA waveform, provides a kind of slow-time MIMO radar range ambiguity suppression method based on waveform agile phase coding, this method adopts pulse-agile phase coding (Pulse-agile Phase- coded, PAPC) technology, which can obtain range gating performance, so that when the pulse repetition frequency of the waveform is increased, the unambiguous ranging range of the waveform remains unchanged. At the same time, the intra-pulse coding of each pulse is agile, but the carrier frequency is the same, and pulse-Doppler processing can still be performed. Therefore, the speed measurement range of the DDMA waveform can be increased and the DDMA can be improved while keeping the range of the system without ambiguity. The impact of the speed range reduction caused by the Doppler sub-band division of the waveform on the radar target detection performance.

本发明的技术解决方案是：Technical solution of the present invention is:

一种基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制方法，该方法的步骤包括：A slow-time MIMO radar range ambiguity suppression method based on waveform agile phase encoding, the steps of the method include:

步骤S1，建立PAPC-DDMA信号模型，并对所建立的PAPC-DDMA信号模型进行优化，得到优化后的PAPC-DDMA信号模型；Step S1, establishing a PAPC-DDMA signal model, and optimizing the established PAPC-DDMA signal model to obtain an optimized PAPC-DDMA signal model;

步骤S2，设置步骤S1得到的优化后的PAPC-DDMA信号模型中的目标参数，得到各接收天线的回波信号；Step S2, setting the target parameters in the optimized PAPC-DDMA signal model obtained in step S1, to obtain the echo signals of each receiving antenna;

步骤S3，对步骤S2得到的各接收天线的回波信号进行多距离段联合脉冲-多普勒处理，得到各接收天线对应的无距离模糊的多距离段综合距离-多普勒平面；Step S3, performing multi-range joint pulse-Doppler processing on the echo signals of each receiving antenna obtained in step S2, to obtain a multi-range comprehensive range-Doppler plane corresponding to each receiving antenna without range ambiguity;

步骤S4，利用多普勒滤波器对步骤S3中得到的各接收天线对应的无距离模糊的多距离段综合距离-多普勒平面进行MIMO解调，得到解调后的各个MIMO收-发通道对应的多距离段综合距离-多普勒平面；Step S4, using the Doppler filter to perform MIMO demodulation on the multi-range comprehensive range-Doppler plane without distance ambiguity corresponding to each receiving antenna obtained in step S3, and obtain each MIMO receiving-transmitting channel after demodulation Corresponding multi-range integrated range-Doppler plane;

步骤S5，基于步骤S4解调后的各个MIMO收-发通道对应的多距离段综合距离-多普勒平面进行恒虚警率(CFAR)检测，得到无模糊的目标距离信息和目标速度信息。Step S5, performing constant false alarm rate (CFAR) detection based on the multi-range comprehensive range-Doppler plane corresponding to each MIMO receiving-transmitting channel demodulated in step S4, to obtain unambiguous target distance information and target speed information.

所述的步骤S1中，设一个具有M个发射通道和N个接收通道的收发共置式一维天线阵列，阵列中各天线为全向天线，在发射阵列中，第m(m＝0,…,M-1个阵元到参考天线的距离为dm，在接收阵列中，第nn＝0,…,N-1个阵元到参考天线的距离为dn，雷达系统工作频率为f0，工作波长为λ0，在一个相参处理周期(Coherent processing interval,CPI)内有K个脉冲，雷达系统的PRT为Tr，对应的PRF为fr＝1/Tr，DDMA波形通过对各通道进行慢时间初相编码，将完整的距离-多普勒平面分成M个谱宽为Δfsub＝fr/M的多普勒子带，慢时间初相编码

Figure BDA0003828745460000031
是发射通道编号m与脉冲编号k(k＝0,…,K-1)的函数，则t时刻第m个发射天线的PAPC-DDMA信号模型sm(t)为：In the step S1, a co-located one-dimensional antenna array of transmitting and receiving with M transmit channels and N receive channels is set, and each antenna in the array is an omnidirectional antenna. In the transmit array, the mth (m=0,... , the distance from M-1 array elements to the reference antenna is dm, in the receiving array, the distance from nn=0,...,N-1 array elements to the reference antenna is d n , and the operating frequency of the radar system is f 0 , The working wavelength is λ 0 , there are K pulses in a coherent processing interval (CPI), the PRT of the radar system is T r , and the corresponding PRF is f r =1/T r , the DDMA waveform passes through each The channel performs slow-time initial phase encoding, divides the complete range-Doppler plane into M Doppler subbands with a spectral width of Δf sub = f r /M, and slow-time initial phase encoding
Figure BDA0003828745460000031
is the function of the transmit channel number m and the pulse number k (k=0,...,K-1), then the PAPC-DDMA signal model s m (t) of the mth transmit antenna at time t is:

Figure BDA0003828745460000032
Figure BDA0003828745460000032

其中，upulse(t-kTr)为t时刻第k个脉冲的基带脉内调制信号，

Figure BDA0003828745460000033
αm为第m个通道所发射的基带信号所在的多普勒中心频率：Among them, u pulse (t-kT r ) is the baseband intrapulse modulation signal of the kth pulse at time t,
Figure BDA0003828745460000033
α m is the Doppler center frequency of the baseband signal transmitted by the mth channel:

Figure BDA0003828745460000034
Figure BDA0003828745460000034

所述的步骤S1中，对所建立的PAPC-DDMA信号模型进行优化是指优化PAPC-DDMA信号模型中的upulse(t)，得到连续相位PAPC波形集

Figure BDA0003828745460000035
具体优化步骤为：In the described step S1, optimizing the established PAPC-DDMA signal model refers to optimizing u pulse (t) in the PAPC-DDMA signal model to obtain a continuous phase PAPC waveform set
Figure BDA0003828745460000035
The specific optimization steps are:

假设一帧PAPC编码信号集内具有Q组不同的连续相位编码信号，每个编码信号的码长为P比特，则第q组相位编码信号的脉内调制波形

Figure BDA0003828745460000036
表示为：Assuming that there are Q groups of different continuous phase coded signals in a frame of PAPC coded signal set, and the code length of each coded signal is P bits, then the intrapulse modulation waveform of the qth group of phase coded signals
Figure BDA0003828745460000036
Expressed as:

Figure BDA0003828745460000037
Figure BDA0003828745460000037

其中，{cqp},(p＝0,…,P-1)为第q组相位编码信号的编码序列，τc为码片宽度，即相邻两码片的时间间隔，由此得t时刻，一帧PAPC编码信号集的基带参考信号模型为：Among them, {c qp }, (p=0,...,P-1) is the coding sequence of the qth group of phase coding signals, τc is the chip width, that is, the time interval between two adjacent chips, thus t At time, the baseband reference signal model of a frame of PAPC coded signal set is:

Figure BDA0003828745460000041
Figure BDA0003828745460000041

对所建立的PAPC-DDMA信号模型进行优化是指优化编码序列{cqp}，保证各编码序列具有较低的自相关旁瓣峰值ASP(cq)，各编码序列之间具有较低的互相关旁瓣峰值

Figure BDA0003828745460000042
其中，q1≠q2。Optimizing the established PAPC-DDMA signal model refers to optimizing the coding sequence {c qp } to ensure that each coding sequence has a lower autocorrelation sidelobe peak ASP(c q ), and each coding sequence has a lower cross-correlation Correlated sidelobe peaks
Figure BDA0003828745460000042
Wherein, q 1 ≠q 2 .

首先随机初始化连续相位编码序列集，码组数为Q，码长为P，相位为θqp，其表达式为：Firstly, the continuous phase coding sequence set is randomly initialized, the number of code groups is Q, the code length is P, and the phase is θ qp , the expression is:

Figure BDA0003828745460000043
Figure BDA0003828745460000043

完成初始化后，设定代价函数，将自相关旁瓣峰值和互相关旁瓣峰值作为码集性能的衡量标准，构建的码集对应的代价函数Φ(C)如下：After the initialization is completed, set the cost function, and use the peak value of the autocorrelation sidelobe and the peak value of the cross-correlation sidelobe as the performance standard of the code set. The cost function Φ(C) corresponding to the constructed code set is as follows:

Figure BDA0003828745460000044
Figure BDA0003828745460000044

其中，λ为设定权重，ASP(cq)为码集中第q个码元序列cq的自相关旁瓣峰值，计算公式如下：Among them, λ is the set weight, ASP(c q ) is the autocorrelation sidelobe peak value of the qth symbol sequence c q in the code set, and the calculation formula is as follows:

Figure BDA0003828745460000045
Figure BDA0003828745460000045

A(cq,k)表示码集中序列cq的自相关函数，数学表达式为：A(c q ,k) represents the autocorrelation function of the sequence c q in the code set, and the mathematical expression is:

Figure BDA0003828745460000046
Figure BDA0003828745460000046

上标*表示复共轭，

Figure BDA0003828745460000047
为码集中第q1和第q2码元序列
Figure BDA0003828745460000048
和
Figure BDA0003828745460000049
的互相关旁瓣峰值，计算公式如下：The superscript * indicates complex conjugation,
Figure BDA0003828745460000047
is the q 1 and q 2 symbol sequences in the code set
Figure BDA0003828745460000048
with
Figure BDA0003828745460000049
The cross-correlation sidelobe peak value of , the calculation formula is as follows:

Figure BDA0003828745460000051
Figure BDA0003828745460000051

Figure BDA0003828745460000052
表示码集中序列
Figure BDA0003828745460000053
和
Figure BDA0003828745460000054
的互相关函数，数学表达式为：
Figure BDA0003828745460000052
Represents the sequence in the code set
Figure BDA0003828745460000053
with
Figure BDA0003828745460000054
The cross-correlation function of , the mathematical expression is:

Figure BDA0003828745460000055
Figure BDA0003828745460000055

Figure BDA0003828745460000056
Figure BDA0003828745460000056

对连续相位编码序列集进行局部搜索，每次迭代将各编码序列中的每个码元作为当前码元进行相位替换，并计算新的代价函数，若替换相位值对应的代价函数小于原始相位值对应的代价函数，则将当前替换的相位值作为当前码元的相位值，否则，保持当前码元的原始相位值不变，当迭代次数达到预先设定的最大值或代价函数满足阈值时，停止搜索迭代的过程，得到优化后的连续相位编码序列集。Perform a local search on the set of continuous phase encoding sequences, replace each symbol in each encoding sequence as the current symbol in each iteration, and calculate a new cost function, if the cost function corresponding to the replacement phase value is smaller than the original phase value For the corresponding cost function, take the currently replaced phase value as the phase value of the current symbol, otherwise, keep the original phase value of the current symbol unchanged, when the number of iterations reaches the preset maximum value or the cost function meets the threshold, The process of searching and iterating is stopped, and the optimized continuous phase encoding sequence set is obtained.

至此得到t时刻第m个发射天线优化后的PAPC-DDMA发射信号模型为：So far, the optimized PAPC-DDMA transmit signal model of the mth transmit antenna at time t is:

Figure BDA0003828745460000057
Figure BDA0003828745460000057

其中，TQ＝QTr为PAPC信号的帧周期，令CPI内脉冲数与一帧内PAPC信号个数的比值K/Q为整数；Wherein, T Q =QT r is the frame period of the PAPC signal, making the ratio K/Q of the number of pulses in the CPI and the number of PAPC signals in a frame be an integer;

所述的步骤S2中，设置的目标参数包括位于雷达远场的匀速运动点目标的距离为Rt，目标相对雷达的径向速度为vt，目标多普勒为ft＝2vt/λ0，目标的波达方向为φt，则第n个接收天线得到的第m个发射天线对应的回波信号smn(t)表示为：In the step S2, the set target parameters include the distance of the uniform moving point target located in the far field of the radar as R t , the radial velocity of the target relative to the radar as v t , and the target Doppler as f t =2v t /λ 0 , the direction of arrival of the target is φ t , then the echo signal s mn (t) corresponding to the mth transmitting antenna obtained by the nth receiving antenna is expressed as:

Figure BDA0003828745460000058
Figure BDA0003828745460000058

其中，τmn为回波时延，具有如下形式：Among them, τ mn is the echo delay, which has the following form:

Figure BDA0003828745460000061
Figure BDA0003828745460000061

第n个接收天线的接收信号应为所有M个发射信号之和，经过下变频与低通滤波后，表示为：The received signal of the nth receiving antenna should be the sum of all M transmitted signals. After down-conversion and low-pass filtering, it can be expressed as:

Figure BDA0003828745460000062
Figure BDA0003828745460000062

所述的步骤S3中，对各接收天线得到的回波信号进行多距离段联合脉冲-多普勒处理的方法为：In the step S3, the method of performing multi-distance joint pulse-Doppler processing on the echo signals obtained by each receiving antenna is as follows:

步骤S31，使用不同的接收滤波器组对接收信号进行匹配滤波处理，得到不同距离段对应的匹配滤波输出结果，对于第q(q＝0,…,Q-1)个距离段对应的接收滤波器组hq(t)，为PAPC编码信号集基带参考信号uref(t)循环移位q个脉冲后得到，则第q个距离段对应的匹配滤波输出结果表示为：Step S31, use different receive filter banks to perform matched filter processing on the received signal, and obtain matched filter output results corresponding to different distance segments, for the receive filter corresponding to the qth (q=0,...,Q-1) distance segment The device group h q (t) is obtained by cyclically shifting the baseband reference signal u ref (t) of the PAPC coded signal set by q pulses, then the output result of the matched filter corresponding to the qth distance segment is expressed as:

Figure BDA0003828745460000063
Figure BDA0003828745460000063

步骤S32，对步骤S31的第q个距离段匹配滤波输出结果按脉冲重复周期重排，作慢时间脉冲-多普勒处理，即沿慢时间进行加窗、补零，并作离散傅里叶变换，得到各距离段对应的距离-多普勒平面，将各距离段对应的距离-多普勒平面依次拼接，得到多距离段综合距离-多普勒平面；Step S32, rearrange the output results of the matched filter of the qth range segment in step S31 according to the pulse repetition period, and perform slow time pulse-Doppler processing, that is, perform windowing and zero padding along the slow time, and perform discrete Fourier transform Transform to obtain the range-Doppler plane corresponding to each range segment, and splice the range-Doppler plane corresponding to each range segment in turn to obtain the comprehensive range-Doppler plane of multiple range segments;

对第q个距离段匹配滤波输出结果

Figure BDA0003828745460000064
按脉冲数重排，进行L点FFT处理，结果具有如下形式：Matching filter output results for the qth distance segment
Figure BDA0003828745460000064
Rearrange according to the number of pulses, and perform L-point FFT processing, and the result has the following form:

Figure BDA0003828745460000065
Figure BDA0003828745460000065

其中，w(k)为慢时间加窗函数权值，用来抑制速度维旁瓣，

Figure BDA0003828745460000066
为第q个距离段匹配滤波输出结果的第k个脉冲，l＝0,…,L-1表示第l个速度通道的输出，将各距离段对应的脉冲-多普勒处理结果依次拼接，得到多距离段综合距离-多普勒平面，即：Among them, w(k) is the weight of the slow time windowing function, which is used to suppress the side lobe of the velocity dimension,
Figure BDA0003828745460000066
It is the kth pulse of the matched filter output result of the qth distance segment, l=0,...,L-1 represents the output of the lth velocity channel, and the pulse-Doppler processing results corresponding to each distance segment are sequentially spliced, The comprehensive range-Doppler plane of multiple range segments is obtained, namely:

Figure BDA0003828745460000071
Figure BDA0003828745460000071

所述的步骤S4中，利用多普勒滤波器对各接收天线对应的无距离模糊的多距离段综合距离-多普勒平面进行MIMO解调的方法为：In the described step S4, the method for performing MIMO demodulation on the multi-range comprehensive range-Doppler plane without range ambiguity corresponding to each receiving antenna by using the Doppler filter is:

PAPC-DDMA的MIMO解调通过多普勒低通滤波来实现，利用第i个发射通道对应的多普勒频率中心αi对

Figure BDA0003828745460000072
进行混频，将第i个发射通道对应的回波混频至零多普勒：The MIMO demodulation of PAPC-DDMA is realized by Doppler low-pass filtering, using the Doppler frequency center α i pair corresponding to the i-th transmit channel
Figure BDA0003828745460000072
Perform frequency mixing to mix the echo corresponding to the i-th transmit channel to zero Doppler:

Figure BDA0003828745460000073
Figure BDA0003828745460000073

之后，利用截止频率为[-Δfsub/2,Δfsub/2]的低通滤波器对

Figure BDA0003828745460000074
进行低通滤波，得到第(n,i)个收-发通道对应的多距离段综合距离-多普勒平面：Afterwards, using a low-pass filter pair with a cutoff frequency of [-Δf sub /2, Δf sub /2]
Figure BDA0003828745460000074
Perform low-pass filtering to obtain the multi-range comprehensive range-Doppler plane corresponding to the (n,i)th receiving-transmitting channel:

Figure BDA0003828745460000075
Figure BDA0003828745460000075

其中，HLP(t,l)为低通滤波器的时域响应，以此类推，可以得到各个MIMO收-发通道对应的多距离段综合距离-多普勒平面，实现MIMO解调。Among them, H LP (t,l) is the time-domain response of the low-pass filter, and so on, the multi-range comprehensive range-Doppler plane corresponding to each MIMO receiving-transmitting channel can be obtained to realize MIMO demodulation.

有益效果Beneficial effect

本发明提出一种基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制方法。具有如下有益效果：The invention proposes a range ambiguity suppression method for slow time MIMO radar based on waveform agile phase encoding. It has the following beneficial effects:

(1)本发明的方法中，PAPC-DDMA信号模型采用脉间码型捷变技术，使传统DDMA波形获得距离选通性，从而在提高波形的PRF时，保持波形的无模糊测距范围不变。(1) In the method of the present invention, PAPC-DDMA signal model adopts inter-pulse code type agility technology, makes traditional DDMA waveform obtain distance gating property, thereby when improving the PRF of waveform, the unambiguous ranging range of keeping waveform is not Change.

(2)本发明的方法中，优化后的PAPC-DDMA信号模型采用局部搜索算法，提高随机相位编码序列集的自相关、互相关性能。(2) In the method of the present invention, the optimized PAPC-DDMA signal model adopts a local search algorithm to improve the autocorrelation and cross-correlation performance of the random phase encoding sequence set.

(3)本发明的方法中，采用基于参考信号时延的PAPC-DDMA波形多距离段联合脉冲-多普勒处理方法，得到无距离模糊的多距离段综合距离-多普勒平面。(3) In the method of the present invention, the PAPC-DDMA waveform multi-range segment joint pulse-Doppler processing method based on the reference signal time delay is adopted to obtain the comprehensive range-Doppler plane of the multi-range segment without range ambiguity.

(4)本发明较好地解决了常规DDMA波形在高重频应用下产生的距离模糊问题，同时可有效提升DDMA波形的无模糊测速范围，提高慢时间MIMO雷达对高速运动目标的探测性能。通过仿真实验验证了PAPC-DDMA波形的距离选通性及目标距离模糊抑制效果。(4) The present invention better solves the range ambiguity problem caused by conventional DDMA waveforms under high repetition frequency applications, and can effectively improve the unambiguous speed measurement range of DDMA waveforms, and improve the detection performance of slow-time MIMO radars for high-speed moving targets. The range gating property of PAPC-DDMA waveform and the suppression effect of target range ambiguity are verified by simulation experiments.

附图说明Description of drawings

图1为本发明PAPC-DDMA信号波形示意图；Fig. 1 is the PAPC-DDMA signal waveform schematic diagram of the present invention;

图2为本发明PAPC-DDMA信号距离选通示意图；Fig. 2 is a schematic diagram of PAPC-DDMA signal distance gating of the present invention;

图3为本发明方法信号处理流程图；Fig. 3 is the flow chart of signal processing of the method of the present invention;

图4为PAPC-DDMA信号多距离段综合距离-多普勒平面；Fig. 4 is PAPC-DDMA signal multi-distance segment integrated range-Doppler plane;

图5为LFM-DDMA信号距离-多普勒平面；Fig. 5 is LFM-DDMA signal range-Doppler plane;

图6为PAPC-DDMA各目标所在速度通道一维距离像；Fig. 6 is a one-dimensional distance image of the speed channel where each target of PAPC-DDMA is located;

图7为LFM-DDMA各目标所在速度通道一维距离像；Fig. 7 is a one-dimensional distance image of the velocity channel where each target of LFM-DDMA is located;

图8为PAPC-DDMA各目标所在距离单元速度谱；Fig. 8 is the velocity spectrum of the range unit where each target of PAPC-DDMA is located;

图9为LFM-DDMA各目标所在距离单元速度谱。Fig. 9 is the velocity spectrum of the range unit where each target of LFM-DDMA is located.

具体实施方式detailed description

为使本发明的目的、技术方案和优点更加清楚明白，以下结合具体实例，并参照附图，对本发明进一步详细说明。In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific examples and with reference to the accompanying drawings.

本发明提出的基于波形捷变相位编码的慢时间MIMO雷达距离模糊抑制方法，如图3所示，步骤如下：The slow-time MIMO radar range ambiguity suppression method based on waveform agility phase coding proposed by the present invention, as shown in Figure 3, the steps are as follows:

步骤S1，建立PAPC-DDMA信号模型，并优化随机连续相位编码波形集；Step S1, establishing a PAPC-DDMA signal model, and optimizing a random continuous phase encoding waveform set;

所述步骤S1还包括如下步骤：Said step S1 also includes the following steps:

步骤S11，设一个具有M个发射通道和N个接收通道的收发共置式一维天线阵列，阵列中各天线为全向天线。在发射阵列中，第m(m＝0,…,M-1)个阵元到参考天线的距离为dm。类似地，在接收阵列中，第n(n＝0,…,N-1)个阵元到参考天线的距离为dn。注意此处使用的对阵元间距的定义方式更具有普遍性，可适用于均匀与非均匀阵列。雷达系统工作频率为f0，工作波长为λ0。在一个相参处理周期(Coherent processing interval,CPI)内有K个脉冲。雷达系统的PRT为Tr，对应的PRF为fr＝1/Tr。In step S11, a co-located one-dimensional antenna array with M transmit channels and N receive channels is set, and each antenna in the array is an omnidirectional antenna. In the transmitting array, the distance from the mth (m=0, . . . , M−1) array element to the reference antenna is 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 element spacing used here is more general and applies to both uniform and non-uniform arrays. The operating frequency of the radar system is f 0 and the operating wavelength is λ 0 . There are K pulses in a coherent processing interval (CPI). The PRT of the radar system is T r , and the corresponding PRF is f r =1/T r .

DDMA波形通过对各通道进行慢时间初相编码，将完整的距离-多普勒平面分成M个谱宽为Δfsub＝fr/M的多普勒子带，并将各通道发射波形调制到不同的多普勒子带中，实现MIMO正交发射。慢时间初相编码

Figure BDA0003828745460000091
是发射通道编号m与脉冲编号k(k＝0,…,K-1)的函数。则第m个发射天线对应的发射波形可以表示为：The DDMA waveform divides the complete range-Doppler plane into M Doppler sub-bands with a spectral width of Δf sub = f r /M by encoding each channel with a slow time initial phase, and modulates the transmit waveform of each channel to In different Doppler sub-bands, MIMO orthogonal transmission is realized. slow time initial phase encoding
Figure BDA0003828745460000091
It is a function of the transmission channel number m and the pulse number k (k=0,...,K-1). Then the transmit waveform corresponding to the mth transmit antenna can be expressed as:

Figure BDA0003828745460000092
Figure BDA0003828745460000092

其中，upulse(t)为各脉冲的基带脉内调制信号。令慢时间初相函数具有如下形式：Among them, u pulse (t) is the baseband intra-pulse modulation signal of each pulse. Let the slow time initial phase function have the following form:

Figure BDA0003828745460000093
Figure BDA0003828745460000093

则第m个通道所发射的基带信号将被调制到多普勒中心为αm的子带内。令各子带的多普勒中心αm具有如下形式：Then the baseband signal transmitted by the mth channel will be modulated into the subband whose Doppler center is α m . Let the Doppler center α m of each subband have the following form:

Figure BDA0003828745460000094
Figure BDA0003828745460000094

至此，第m个通道所发射的基带信号被调制到多普勒中心为αm，谱宽为Δfsub的多普勒子带中。So far, the baseband signal transmitted by the mth channel is modulated into the Doppler sub-band whose Doppler center is α m and the spectral width is Δf sub .

传统DDMA波形脉内调制采用线性调频信号，即：The traditional DDMA waveform intra-pulse modulation uses a linear frequency modulation signal, namely:

Figure BDA0003828745460000095
Figure BDA0003828745460000095

其中B为信号带宽，tp为信号脉宽。本发明方法采用连续相位PAPC波形作为脉内调制信号。假设一帧PAPC编码信号集

Figure BDA0003828745460000096
内具有Q组不同的连续相位编码信号，每个编码信号的码长为P比特。则第q组相位编码信号的脉内调制波形
Figure BDA0003828745460000097
可以表示为：Among them, B is the signal bandwidth, and t p is the signal pulse width. The method of the invention adopts the continuous phase PAPC waveform as the intrapulse modulation signal. Suppose a frame of PAPC coded signal set
Figure BDA0003828745460000096
There are Q groups of different continuous phase coded signals, and the code length of each coded signal is P bits. Then the intrapulse modulation waveform of the qth group of phase encoding signals
Figure BDA0003828745460000097
It can be expressed as:

Figure BDA0003828745460000098
Figure BDA0003828745460000098

其中{cqp},(p＝0,…,P-1)为第q组相位编码信号的编码序列，τc为码片宽度，即相邻两码片的时间间隔。由此可得一帧PAPC编码信号集的基带参考信号模型为：Where {c qp }, (p=0,...,P-1) is the coding sequence of the qth group of phase coding signals, and τ c is the chip width, that is, the time interval between two adjacent chips. From this, the baseband reference signal model of a frame of PAPC coded signal set can be obtained as:

Figure BDA0003828745460000101
Figure BDA0003828745460000101

将(5)式表示的PAPC脉内调制波形带入(1)式中，即可得到第m个发射天线对应的PAPC-DDMA发射信号模型：Bring the PAPC intra-pulse modulation waveform represented by (5) into (1), and the PAPC-DDMA transmit signal model corresponding to the mth transmit antenna can be obtained:

Figure BDA0003828745460000102
Figure BDA0003828745460000102

其中TQ＝QTr为PAPC信号的帧周期，选定CPI内脉冲数与一帧内PAPC信号个数的比值K/Q为整数以简化模型。PAPC-DDMA信号的波形调制示意图如图1所示。Where T Q =QT r is the frame period of the PAPC signal, and the ratio K/Q of the number of pulses in the CPI to the number of PAPC signals in one frame is selected as an integer to simplify the model. The schematic diagram of waveform modulation of PAPC-DDMA signal is shown in Figure 1.

步骤S12，优化随机连续相位编码序列集{cqp}，保证各编码序列具有较低的自相关旁瓣峰值ASP(cq)，各编码序列之间具有较低的互相关旁瓣峰值

Figure BDA0003828745460000103
其中，q1≠q2。首先随机初始化连续相位编码波形集，码组数为Q，码长为P，相位为θqp，其表达式为：Step S12, optimize the set of random continuous phase coded sequences {c qp } to ensure that each coded sequence has a lower autocorrelation sidelobe peak value ASP(c q ), and each coded sequence has a lower cross-correlation sidelobe peak value
Figure BDA0003828745460000103
Wherein, q 1 ≠q 2 . First, the continuous phase encoding waveform set is randomly initialized, the number of code groups is Q, the code length is P, and the phase is θ qp , the expression is:

Figure BDA0003828745460000104
Figure BDA0003828745460000104

完成初始化后，设定代价函数，本发明将自相关旁瓣峰值和互相关旁瓣峰值作为码集性能的衡量标准，构建的码集对应的代价函数Φ(C)如下：After completing the initialization, set the cost function, the present invention uses the autocorrelation sidelobe peak value and the cross-correlation sidelobe peak value as the measure standard of the code set performance, and the corresponding cost function Φ (C) of the code set constructed is as follows:

Figure BDA0003828745460000105
Figure BDA0003828745460000105

其中，λ为设定权重，ASP(cq)为码集中第q个码元序列cq的自相关旁瓣峰值，计算公式如下：Among them, λ is the set weight, ASP(c q ) is the autocorrelation sidelobe peak value of the qth symbol sequence c q in the code set, and the calculation formula is as follows:

Figure BDA0003828745460000106
Figure BDA0003828745460000106

A(cq,k)表示码集中序列cq的自相关函数，数学表达式为：A(c q ,k) represents the autocorrelation function of the sequence c q in the code set, and the mathematical expression is:

Figure BDA0003828745460000107
Figure BDA0003828745460000107

上标*表示复共轭，

Figure BDA0003828745460000108
为码集中第q1和第q2码元序列
Figure BDA0003828745460000109
和
Figure BDA00038287454600001010
的互相关旁瓣峰值，计算公式如下：The superscript * indicates complex conjugation,
Figure BDA0003828745460000108
is the q 1 and q 2 symbol sequences in the code set
Figure BDA0003828745460000109
with
Figure BDA00038287454600001010
The cross-correlation sidelobe peak value of , the calculation formula is as follows:

Figure BDA00038287454600001011
Figure BDA00038287454600001011

Figure BDA0003828745460000111
表示码集中序列
Figure BDA0003828745460000112
和
Figure BDA0003828745460000113
的互相关函数，数学表达式为：
Figure BDA0003828745460000111
Represents the sequence in the code set
Figure BDA0003828745460000112
with
Figure BDA0003828745460000113
The cross-correlation function of , the mathematical expression is:

Figure BDA0003828745460000114
Figure BDA0003828745460000114

对连续相位编码序列集进行局部搜索，每次迭代将各编码序列中的每个码元作为当前码元进行相位替换，并计算新的代价函数，若替换相位值对应的代价函数小于原始相位值对应的代价函数，则将当前替换的相位值作为当前码元的相位值，否则，保持当前码元的原始相位值不变，当迭代次数达到预先设定的最大值或代价函数满足阈值时，停止搜索迭代的过程，得到优化后的连续相位编码序列集。Perform a local search on the set of continuous phase encoding sequences, replace each symbol in each encoding sequence as the current symbol in each iteration, and calculate a new cost function, if the cost function corresponding to the replacement phase value is smaller than the original phase value For the corresponding cost function, take the currently replaced phase value as the phase value of the current symbol, otherwise, keep the original phase value of the current symbol unchanged, when the number of iterations reaches the preset maximum value or the cost function meets the threshold, The process of searching and iterating is stopped, and the optimized continuous phase encoding sequence set is obtained.

步骤S2，系统及目标参数初始化，根据目标参数设置回波时延，得到各通道PAPC-DDMA接收信号；Step S2, initializing the system and target parameters, setting the echo delay according to the target parameters, and obtaining the PAPC-DDMA receiving signals of each channel;

假设一个位于雷达远场的匀速运动点目标的距离为Rt，目标相对雷达的径向速度为vt，对应目标多普勒为ft＝2vt/λ0，目标的波达方向为φt。则第n个接收天线得到的第m个发射天线对应的回波信号smn(t)可以表示为：Assume that the distance of a uniform moving point target located in the far field of the radar is R t , the radial velocity of the target relative to the radar is v t , the corresponding Doppler of the target is f t = 2v t /λ 0 , and the direction of arrival of the target is φ t . Then the echo signal s mn (t) corresponding to the mth transmitting antenna obtained by the nth receiving antenna can be expressed as:

Figure BDA0003828745460000115
Figure BDA0003828745460000115

其中，τmn为回波时延，具有如下形式：Among them, τ mn is the echo delay, which has the following form:

Figure BDA0003828745460000116
Figure BDA0003828745460000116

进一步地，第n个接收天线的接收信号应为所有M个发射信号之和，经过下变频与低通滤波后，可以表示为：Furthermore, the received signal of the nth receiving antenna should be the sum of all M transmitted signals, after down-conversion and low-pass filtering, it can be expressed as:

Figure BDA0003828745460000117
Figure BDA0003828745460000117

步骤S3，对各接收天线得到的回波信号进行多距离段联合脉冲-多普勒处理，得到无距离模糊的多距离段综合距离-多普勒平面；Step S3, performing multi-range joint pulse-Doppler processing on the echo signals obtained by each receiving antenna to obtain a multi-range comprehensive range-Doppler plane without range ambiguity;

所述步骤S3还包括如下步骤：Said step S3 also includes the following steps:

步骤S31，使用不同的接收滤波器组对接收信号进行匹配滤波处理，得到不同距离段对应的匹配滤波输出结果。理论上，一帧具有Q组不同码型的PAPC编码信号集，可以实现最多Q个距离段的无模糊探测，PAPC-DDMA信号的距离选通性如图2图所示。由图2可以看出，对于第q(q＝0,…,Q-1)个距离段对应的接收滤波器组hq(t)，应为PAPC编码信号集基带参考信号uref(t)循环移位q个脉冲后得到。则第q个距离段对应的匹配滤波输出结果可以表示为：In step S31, different receiving filter banks are used to perform matched filtering processing on the received signal to obtain matched filtering output results corresponding to different distance segments. Theoretically, one frame has Q sets of PAPC coded signal sets of different code types, which can realize unambiguous detection of up to Q range segments. The range gating of PAPC-DDMA signals is shown in Figure 2. It can be seen from Fig. 2 that for the receiving filter bank h q (t) corresponding to the qth (q=0,...,Q-1) distance segment, it should be the PAPC coded signal set baseband reference signal u ref (t) It is obtained after a cyclic shift of q pulses. Then the matched filter output corresponding to the qth distance segment can be expressed as:

Figure BDA0003828745460000121
Figure BDA0003828745460000121

步骤S32，对上述第q个距离段匹配滤波输出结果按脉冲重复周期重排，作慢时间脉冲-多普勒处理，即沿慢时间进行加窗、补零，并作离散傅里叶变换，得到各距离段对应的距离-多普勒平面。将各距离段对应的距离-多普勒平面依次拼接，得到多距离段综合距离-多普勒平面。Step S32, rearranging the output results of the matched filter for the above qth distance segment according to the pulse repetition period, performing slow time pulse-Doppler processing, that is, performing windowing, zero padding along the slow time, and performing discrete Fourier transform, The range-Doppler plane corresponding to each range segment is obtained. The range-Doppler planes corresponding to each range segment are sequentially spliced to obtain the comprehensive range-Doppler plane of multiple range segments.

对第q个距离段匹配滤波输出结果

Figure BDA0003828745460000122
按脉冲数重排，进行L点FFT处理，结果具有如下形式：Matching filter output results for the qth distance segment
Figure BDA0003828745460000122
Rearrange according to the number of pulses, and perform L-point FFT processing, and the result has the following form:

Figure BDA0003828745460000123
Figure BDA0003828745460000123

其中，w(k)为慢时间加窗函数权值，用来抑制速度维旁瓣，

Figure BDA0003828745460000124
为第q个距离段匹配滤波输出结果的第k个脉冲，l＝0,…,L-1表示第l个速度通道的输出。将各距离段对应的脉冲-多普勒处理结果依次拼接，得到多距离段综合距离-多普勒平面，即：Among them, w(k) is the weight of the slow time windowing function, which is used to suppress the side lobe of the velocity dimension,
Figure BDA0003828745460000124
is the kth pulse of the matched filter output result of the qth distance segment, and l=0,...,L-1 represents the output of the lth velocity channel. The pulse-Doppler processing results corresponding to each range segment are sequentially spliced to obtain the comprehensive range-Doppler plane of multiple range segments, namely:

Figure BDA0003828745460000125
Figure BDA0003828745460000125

步骤S4，利用多普勒滤波器对步骤S3中得到的各接收天线对应的多距离段综合距离-多普勒平面进行MIMO解调，得到解调后的各个MIMO收-发通道对应的多距离段综合距离-多普勒平面；Step S4, using the Doppler filter to perform MIMO demodulation on the multi-range comprehensive range-Doppler plane corresponding to each receiving antenna obtained in step S3, and obtain the multi-range corresponding to each MIMO receiving-transmitting channel after demodulation Segment integrated distance-Doppler plane;

PAPC-DDMA的MIMO解调可以通过简单的多普勒低通滤波来实现。为了分离第i个发射天线在第n个接收天线对应的多距离段综合距离-多普勒平面上的响应，利用第i个发射通道对应的多普勒频率中心αi对

Figure BDA0003828745460000126
进行混频，将第i个发射通道对应的回波混频至零多普勒：MIMO demodulation of PAPC-DDMA can be realized by simple Doppler low-pass filtering. In order to separate the response of the i-th transmitting antenna on the multi-range integrated range-Doppler plane corresponding to the n-th receiving antenna, the Doppler frequency center α i corresponding to the i-th transmitting channel is used to pair
Figure BDA0003828745460000126
Perform frequency mixing to mix the echo corresponding to the i-th transmit channel to zero Doppler:

Figure BDA0003828745460000131
Figure BDA0003828745460000131

之后，利用截止频率为[-Δfsub/2,Δfsub/2]的低通滤波器对

Figure BDA0003828745460000132
进行低通滤波，得到第(n,i)个收-发通道对应的多距离段综合距离-多普勒平面：Afterwards, using a low-pass filter pair with a cutoff frequency of [-Δf sub /2, Δf sub /2]
Figure BDA0003828745460000132
Perform low-pass filtering to obtain the multi-range comprehensive range-Doppler plane corresponding to the (n,i)th receiving-transmitting channel:

Figure BDA0003828745460000133
Figure BDA0003828745460000133

其中，HLP(t,l)为低通滤波器的时域响应。以此类推，可以得到各个MIMO收-发通道对应的多距离段综合距离-多普勒平面，实现MIMO解调。where H LP (t,l) is the time-domain response of the low-pass filter. By analogy, the multi-range integrated range-Doppler plane corresponding to each MIMO receiving-transmitting channel can be obtained to realize MIMO demodulation.

步骤S5，基于多距离段综合距离-多普勒平面进行恒虚警率(CFAR)检测，得到目标距离、速度信息。Step S5, performing constant false alarm rate (CFAR) detection based on the multi-distance integrated range-Doppler plane to obtain target distance and speed information.

下面给出使用上述方法，对目标进行距离模糊抑制的实施例。An example of performing distance blur suppression on a target using the above method is given below.

实施例Example

慢时间MIMO雷达系统为S波段，天线为收发共置6阵元一维线阵。雷达发射PAPC-DDMA波形，其中脉内调制的PAPC波形采用400位，256组的随机连续相位编码波形集。同时，与传统脉内调制为线性调频(Linear Frequency Modulated,LFM)信号的LFM-DDMA波形的目标检测结果进行对比，验证PAPC-DDMA波形的距离选通性及目标距离模糊抑制效果。The slow-time MIMO radar system is S-band, and the antenna is a one-dimensional line array with 6 elements co-located for sending and receiving. The radar transmits PAPC-DDMA waveforms, in which the intra-pulse modulated PAPC waveforms use 400 bits, 256 groups of random continuous phase coded waveform sets. At the same time, compared with the target detection results of the LFM-DDMA waveform whose traditional intra-pulse modulation is a Linear Frequency Modulated (LFM) signal, the range gating performance of the PAPC-DDMA waveform and the suppression effect of the target range ambiguity are verified.

雷达波形参数与雷达目标参数如表1、表2所示；Radar waveform parameters and radar target parameters are shown in Table 1 and Table 2;

表1Table 1

Figure BDA0003828745460000134
Figure BDA0003828745460000134

Figure BDA0003828745460000141
Figure BDA0003828745460000141

表2Table 2

Figure BDA0003828745460000142
Figure BDA0003828745460000142

经过多距离段联合脉冲-多普勒处理后的PAPC-DDMA信号多距离段综合距离-多普勒平面如图4(a)所示，经过MIMO解调后的单通道多距离段综合距离-多普勒平面如图4(b)所示。采用传统LFM-DDMA信号的处理结果如图5所示。可以看出PAPC-DDMA波形具有良好的距离选通性，可以有效抑制各目标在其他距离段处的折叠回波，得到无距离模糊的多距离段联合探测结果。而传统LFM-DDMA信号则会产生距离模糊，目标均会折叠到其他距离段，无法得到准确的目标距离信息。The integrated range-Doppler plane of the PAPC-DDMA signal multi-range segment after multi-range segment joint pulse-Doppler processing is shown in Figure 4(a). The single-channel multi-range segment integrated range after MIMO demodulation- The Doppler plane is shown in Figure 4(b). Figure 5 shows the processing results of traditional LFM-DDMA signals. It can be seen that the PAPC-DDMA waveform has good range gating, which can effectively suppress the folding echo of each target at other ranges, and obtain the multi-range joint detection results without range ambiguity. However, the traditional LFM-DDMA signal will produce range ambiguity, and the target will be folded into other range segments, and accurate target range information cannot be obtained.

PAPC-DDMA与LFM-DDMA信号各目标所在速度通道的一维距离像以及所在距离单元的速度谱分别如图6、图7、图8、图9所示。由图6可以看出PAPC-DDMA信号可以实现无距离模糊的多距离段目标联合探测，而传统LFM-DDMA信号各目标均会在其他距离段形成折叠回波，影响目标的准确检测，如图7所示。经过多距离段联合脉冲-多普勒处理处理后(M＝1024＝30dB)，理论目标信噪比为50dB，PAPC-DDMA波形处理后得到目标信噪比49.7dB，与理论值一致；LFM-DDMA波形处理后得到目标信噪比47.5dB，相比理论值损失2.5dB。由图8和图9可以看出两种信号都可以实现目标速度的有效检测。The one-dimensional range images of the velocity channels of the targets in the PAPC-DDMA and LFM-DDMA signals and the velocity spectra of the range units are shown in Fig. 6, Fig. 7, Fig. 8, and Fig. 9, respectively. It can be seen from Figure 6 that the PAPC-DDMA signal can realize multi-range target joint detection without range ambiguity, while each target of the traditional LFM-DDMA signal will form folded echoes in other range ranges, which will affect the accurate detection of the target, as shown in Fig. 7. After multi-range combined pulse-Doppler processing (M=1024=30dB), the theoretical target SNR is 50dB, and the target SNR is 49.7dB after PAPC-DDMA waveform processing, which is consistent with the theoretical value; LFM- After DDMA waveform processing, the target signal-to-noise ratio is 47.5dB, which is 2.5dB loss compared with the theoretical value. It can be seen from Figure 8 and Figure 9 that both signals can achieve effective detection of the target speed.

由图6还可以看出，PAPC-DDMA信号虽然具有距离选通性，但是各距离段目标会在其他距离段形成较高的副瓣，副瓣水平受相位编码之间的互相关水平约束。在本实施例参数下，400位256组随机离散相位编码经过多距离段联合脉冲-多普勒处理后的互相关副瓣水平为-35dB。It can also be seen from Figure 6 that although the PAPC-DDMA signal has range gating, the targets in each range segment will form higher side lobes in other range segments, and the level of side lobes is constrained by the cross-correlation level between phase codes. Under the parameters of this embodiment, the cross-correlation sidelobe level of the 400-bit 256-group random discrete phase encoding after multi-range joint pulse-Doppler processing is -35dB.

本发明还可有其他多种实施例，以上仅为本发明的较佳实施例而已，并非用于限定本发明的保护范围。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。The present invention can also have other various embodiments, the above are only preferred embodiments of the present invention, and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within 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
Figure FDA0003828745450000011
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:
Figure FDA0003828745450000021
wherein u is pulse (t-kT r ) The baseband intra-pulse modulated signal for the kth pulse at time t,
Figure FDA0003828745450000022
α m the doppler center frequency of the baseband signal transmitted by the mth channel is:
Figure FDA0003828745450000023
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
Figure FDA0003828745450000024
(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
Figure FDA0003828745450000025
Expressed as:
Figure FDA0003828745450000026
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:
Figure FDA0003828745450000027
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:
Figure FDA0003828745450000028
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:
Figure FDA0003828745450000031
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:
Figure FDA0003828745450000032
A(c q k) represents a code-concentrated sequence c q The mathematical expression of the autocorrelation function of (1) is:
Figure FDA0003828745450000033
the superscript denotes the complex conjugate,
Figure FDA0003828745450000034
for the qth of the code set 1 And q th 2 Code element sequence
Figure FDA0003828745450000035
And
Figure FDA0003828745450000036
cross correlation side lobe ofPeak, the mathematical expression is:
Figure FDA0003828745450000037
Figure FDA0003828745450000038
representing code-focused sequences
Figure FDA0003828745450000039
And
Figure FDA00038287454500000310
the mathematical expression is:
Figure FDA00038287454500000311
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:
Figure FDA0003828745450000041
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:
Figure FDA0003828745450000042
wherein, tau mn For echo time delay, it has the following form:
Figure FDA0003828745450000043
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:
Figure FDA0003828745450000044
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:
Figure FDA0003828745450000051
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
Figure FDA0003828745450000052
And (3) rearranging according to the number of pulses, and performing L-point FFT processing, wherein the result has the following form:
Figure FDA0003828745450000053
wherein w (k) is a slow time windowing function weight for suppressing velocity dimension sidelobes,
Figure FDA0003828745450000054
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.:
Figure FDA0003828745450000055
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
Figure FDA0003828745450000056
And mixing, namely mixing the echoes corresponding to the ith transmitting channel to zero Doppler:
Figure FDA0003828745450000061
using a cut-off frequency of [ - Δ f sub /2,Δf sub /2]Low pass filter pair of
Figure FDA0003828745450000062
Low-pass filtering is carried out to obtain a multi-range comprehensive distance-Doppler plane corresponding to the (n, i) th receiving-transmitting channel:
Figure FDA0003828745450000063
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.
CN202211066968.5A 2022-09-01 2022-09-01 Slow-time MIMO radar distance ambiguity suppression method based on waveform agile phase coding Active CN115494469B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202211066968.5A CN115494469B (en) 2022-09-01 2022-09-01 Slow-time MIMO radar distance ambiguity suppression method based on waveform agile phase coding

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211066968.5A CN115494469B (en) 2022-09-01 2022-09-01 Slow-time MIMO radar distance ambiguity suppression method based on waveform agile phase coding

Publications (2)

Publication Number Publication Date
CN115494469A true CN115494469A (en) 2022-12-20
CN115494469B CN115494469B (en) 2024-11-29

Family

ID=84468135

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211066968.5A Active CN115494469B (en) 2022-09-01 2022-09-01 Slow-time MIMO radar distance ambiguity suppression method based on waveform agile phase coding

Country Status (1)

Country Link
CN (1) CN115494469B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116256743A (en) * 2023-05-16 2023-06-13 南京慧尔视智能科技有限公司 Method and device for detecting moving object, electronic equipment and storage medium
CN116482621A (en) * 2023-06-14 2023-07-25 北京理工大学 A Design Method of Phase-Agile Pulse Train Waveform Based on Range Gating Performance Optimization
CN117890898A (en) * 2024-03-01 2024-04-16 清华大学 Bistatic radar encryption target detection method based on phase center agile array
CN118759507A (en) * 2024-09-09 2024-10-11 中南大学 Detection and positioning methods for weak human life signals

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0336273A2 (en) * 1988-04-02 1989-10-11 Daimler-Benz Aerospace Aktiengesellschaft Pulse Doppler radar
JPH06123772A (en) * 1991-09-24 1994-05-06 Shinkichi Nishimoto Encoded pulse doppler radar system
CN106970371A (en) * 2017-04-28 2017-07-21 电子科技大学 A kind of object detection method based on Keystone and matched filtering
CN109946654A (en) * 2019-01-30 2019-06-28 西安电子科技大学 Radar Element-Pulse Coding and Processing Method
CN112834992A (en) * 2021-01-14 2021-05-25 中山大学 Signal processing method, device and storage medium for pulse Doppler radar
CN113640752A (en) * 2021-07-13 2021-11-12 北京理工大学 A Waveform Design Method Based on Interpulse Phase and Spectrum Double Agility
CN114442061A (en) * 2022-01-05 2022-05-06 北京理工大学 Folded clutter suppression method based on range gating and alternative inversion
CN114895261A (en) * 2022-04-07 2022-08-12 西安电子科技大学 Clutter suppression method based on multi-frequency sub-pulse coding array

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0336273A2 (en) * 1988-04-02 1989-10-11 Daimler-Benz Aerospace Aktiengesellschaft Pulse Doppler radar
JPH06123772A (en) * 1991-09-24 1994-05-06 Shinkichi Nishimoto Encoded pulse doppler radar system
CN106970371A (en) * 2017-04-28 2017-07-21 电子科技大学 A kind of object detection method based on Keystone and matched filtering
CN109946654A (en) * 2019-01-30 2019-06-28 西安电子科技大学 Radar Element-Pulse Coding and Processing Method
CN112834992A (en) * 2021-01-14 2021-05-25 中山大学 Signal processing method, device and storage medium for pulse Doppler radar
CN113640752A (en) * 2021-07-13 2021-11-12 北京理工大学 A Waveform Design Method Based on Interpulse Phase and Spectrum Double Agility
CN114442061A (en) * 2022-01-05 2022-05-06 北京理工大学 Folded clutter suppression method based on range gating and alternative inversion
CN114895261A (en) * 2022-04-07 2022-08-12 西安电子科技大学 Clutter suppression method based on multi-frequency sub-pulse coding array

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SHAOQIANG CHANG 等: "Slow-Time MIMO Waveform Design Using Pulse-Agile-Phase-Coding for Range Ambiguity Mitigation", REMOTE SENSING, vol. 15, no. 13, 4 July 2023 (2023-07-04), pages 1 - 18 *
苏峰 等: "基于脉间码型捷变的相位编码旁瓣抑制方法", 北京理工大学学报, no. 05, 15 May 2009 (2009-05-15), pages 441 - 445 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116256743A (en) * 2023-05-16 2023-06-13 南京慧尔视智能科技有限公司 Method and device for detecting moving object, electronic equipment and storage medium
CN116256743B (en) * 2023-05-16 2023-08-04 南京慧尔视智能科技有限公司 Method and device for detecting moving object, electronic equipment and storage medium
CN116482621A (en) * 2023-06-14 2023-07-25 北京理工大学 A Design Method of Phase-Agile Pulse Train Waveform Based on Range Gating Performance Optimization
CN116482621B (en) * 2023-06-14 2023-08-22 北京理工大学 A Design Method of Phase-Agile Pulse Train Waveform Based on Range Gating Performance Optimization
CN117890898A (en) * 2024-03-01 2024-04-16 清华大学 Bistatic radar encryption target detection method based on phase center agile array
CN117890898B (en) * 2024-03-01 2024-05-14 清华大学 Bistatic radar encryption target detection method based on phase center agile array
CN118759507A (en) * 2024-09-09 2024-10-11 中南大学 Detection and positioning methods for weak human life signals

Also Published As

Publication number Publication date
CN115494469B (en) 2024-11-29

Similar Documents

Publication Publication Date Title
CN115494469A (en) A Range Ambiguity Suppression Method for Slow Time MIMO Radar Based on Waveform Agile Phase Coding
CN111880171B (en) Pulse segment coding method for eliminating radar target blind speed
CN116930907B (en) A target coherent accumulation detection method for DDMA-MIMO radar
US8059026B1 (en) Interference avoiding transform domain radar
CN111337914A (en) Extended Doppler FMCW Code Division MIMO Radar
CN101858976B (en) Moving target detection method based on multiple sub-apertures of single-channel SAR
CN102520395B (en) Clutter suppression method based on bistatic multiple-input and multiple-output radar
CN104714231B (en) MIMO SAR imaging method based on complete complementary sequences and phase compensation
CN102608603B (en) Multichannel synthetic aperture radar imaging method based on complete complementary sequence
CN111239721B (en) A Method of Entropy Solution for Velocity Ambiguity of Vehicle-mounted MIMO Radar
CN101452073A (en) Broadband signal synthesizing method based on multi-sending and multi-receiving frequency division radar
Hakobyan Orthogonal frequency division multiplexing multiple-input multiple-output automotive radar with novel signal processing algorithms
BRPI0619296A2 (en) coherent pulse-doppler system, and method of processing a signal received from a target and performing simultaneous measurements of the target range and doppler parameters
Wang et al. Interleaved OFDM radar signals for simultaneous polarimetric measurements
CN103472449B (en) BP wideband synthesis method based on MIMO image domain
CN109212489B (en) An FDA-MIMO Radar Fuzzy Clutter Suppression Method Based on Auxiliary Pulse
CN112965034B (en) Method for improving Doppler tolerance of slow time phase coded signal of sky-wave radar
CN113640752B (en) Waveform design method based on inter-pulse phase frequency spectrum double agility
CN110632573A (en) A space-time two-dimensional keystone transform method for airborne broadband radar
CN104898107A (en) Multiple-input multiple-output synthetic aperture ladar signal processing method
CN114764136A (en) Radar anti-interference waveform generation method based on multi-time scale coupling network
CN114895261A (en) Clutter suppression method based on multi-frequency sub-pulse coding array
CN103605112A (en) Multi-sending-multi-receiving interference synthetic aperture radar time frequency two-dimension signal waveform designing method
CN118566921A (en) Phase coding multi-beam SAR imaging two-dimensional fuzzy inhibition method
Bhattacharjee et al. Multi-carrier wideband OCDM-based THz automotive radar

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant