Design And Optimization Of Orthogonal Waveforms For MIMO Radar

Multiple Input Multiple Output(MIMO)radar is an emerging radar system that uses multiple antennas for signal transmission and reception at both the transmitting and receiving ends,and each transmitting antenna can emit its own signal,thus giving MIMO radar the advantage of waveform diversity.As an important innovation in radar technology,the advantage of waveform diversity enables MIMO radar to overcome the shortcomings of conventional radar modes being relatively fixed,beams being relatively fixed,and waveforms being relatively fixed.It still exhibits excellent detection performance under complex working conditions and can meet the requirements of multiple tasks and purposes.Due to the working mechanism of transmit diversity and receive diversity in MIMO radar,the waveforms transmitted by each antenna have a significant impact on the performance of the radar system.Therefore,the design and optimization of transmit waveforms are of great significance for the MIMO radar system.At present,research on MIMO radar waveforms mainly focuses on two levels: centralized waveform design and distributed waveform design;The centralized MIMO radar is a new type of phased array radar,which adopts a traditional centralized array structure at the transmitter and receiver terminals.Therefore,in centralized MIMO radar,improving the main lobe resolution ability and reducing the sidelobe level are the key to waveform design and optimization.This article mainly studies the performance of centralized MIMO radar,as well as the design and optimization of orthogonal waveforms for frequency modulation and equalization.The specific content of the paper is as follows:1.A signal model of MIMO radar under uniform linear array(ULA)was established,and the virtual aperture characteristics,angular resolution,angle measurement accuracy,and signal-tonoise ratio(SNR)of MIMO radar and PA radar transmission and reception modes were analyzed and compared;Based on this model,two commonly used MIMO radar signal processing methods were further introduced.Elaborated on MIMO radar waveform design and orthogonal waveform optimization.Finally,several main indicators for evaluating MIMO radar waveforms were introduced: radar ambiguity function,emission energy coverage map,and pulse synthesis results.To lay the foundation for the research on waveform design methods carried out later in this article.2.Design and optimize the common waveforms of MIMO radar: Firstly,establish a mathematical model of orthogonal frequency division linear frequency modulation(LFM)signal,analyze the ambiguity function of the LFM signal set,and obtain the frequency interval that minimizes the cross correlation of the signal set,which is then verified through simulation;In response to the problem of high sidelobes in the pulse synthesis results of orthogonal LFM,this paper uses particle swarm optimization to optimize the initial phase of LFM to improve its pulse synthesis results.Then aiming at the problem of high autocorrelation sidelobe and crosscorrelation of phase coded signals in MIMO radar,genetic algorithm and multi CAN algorithm are proposed to optimize the correlation of phase coded signals.The simulation results show that the optimized signal set has good orthogonality.3.In the multi input multi output radar transmission signal,the common modulation method of orthogonal linear frequency modulation signal is single,easy to intercept,and has limited application scenarios;Another common signal is a single carrier frequency phase coded signal,which has a waveform bandwidth of the reciprocal of the sub pulses and is limited in bandwidth,resulting in limited distance resolution;The ambiguity function of general LFM-PC mixed modulation signals has serious "gate lobes".In response to the above issues,this paper proposes a waveform set design method using LFM as the sub pulse,frequency encoding based on permutation sequence,and pseudo random phase encoding composite modulation;Aiming at the poor autocorrelation performance and orthogonality of the composite signal set,an optimization model was constructed,and a multi population optimization genetic algorithm was proposed to optimize it.The simulation results show that the composite signal designed in this paper has high distance resolution,no "gate lobes" in the ambiguity function graph,and the matched filter output pulse width is only affected by the sub pulse bandwidth and is approximately independent of the signal sub pulse width,making it easy to achieve a wideband pulse compression waveform;Compared to genetic algorithms and other optimization algorithms in some literature,multi group optimization genetic algorithms are more efficient,and the optimized composite signal set has good correlation performance.