【摘要】：隨著電磁環(huán)境的復(fù)雜化和人們對(duì)雷達(dá)性能要求的提高,多輸入多輸出(MIMO)雷達(dá)越來(lái)越受到人們關(guān)注。與傳統(tǒng)的相控陣?yán)走_(dá)相比,MIMO雷達(dá)發(fā)射機(jī)的每個(gè)陣元發(fā)射相互正交的波形信號(hào),在接收端通過(guò)對(duì)回波信號(hào)作脈沖壓縮處理來(lái)分離發(fā)射通道,從而增加了自由度,使雷達(dá)性能得到了提升。將MIMO技術(shù)引入機(jī)載雙基地雷達(dá),不但具有上述MIMO雷達(dá)的優(yōu)勢(shì),還具有雙基地帶來(lái)的探測(cè)隱身目標(biāo)、隱蔽偵查等優(yōu)勢(shì)。該系統(tǒng)通過(guò)對(duì)接收機(jī)的回波數(shù)據(jù)進(jìn)行處理,得到了發(fā)射機(jī)與接收機(jī)相對(duì)于目標(biāo)的角度信息,從而降低了傳統(tǒng)配置下雷達(dá)對(duì)時(shí)間同步性的要求。本文將近幾年產(chǎn)生的新技術(shù)--壓縮感知(CS)理論應(yīng)用到MIMO雷達(dá),并針對(duì)雙基地MIMO雷達(dá)的雜波抑制、消除MIMO雷達(dá)發(fā)射波形不理想對(duì)檢測(cè)性能產(chǎn)生的影響以及空時(shí)自適應(yīng)處理(STAP)進(jìn)行了研究。主要工作為如下兩個(gè)方面:1、在實(shí)際中,難以設(shè)計(jì)具有理想相關(guān)性的正交波形,而波形的自相關(guān)與互相關(guān)旁瓣不為零將會(huì)導(dǎo)致雜波協(xié)方差矩陣的估計(jì)造成誤差,進(jìn)而對(duì)雷達(dá)性能產(chǎn)生了嚴(yán)重的影響。針對(duì)這一問(wèn)題,本文首先分析了自相關(guān)和互相關(guān)對(duì)雜波抑制產(chǎn)生影響的原因,其次提出了一種基于壓縮感知的雜波抑制方法。該方法不但在小樣本下具有良好的性能,而且可以有效的消除由于發(fā)射波形不理想對(duì)雜波抑制造成的影響。通過(guò)對(duì)所提方法的性能進(jìn)行仿真分析,驗(yàn)證了該算法能夠有效的消除發(fā)射波形不理想給MIMO雷達(dá)雜波抑制所帶來(lái)的影響。2、由于MIMO雷達(dá)通過(guò)發(fā)射波形分集來(lái)增加虛擬孔徑,使MIMO雷達(dá)系統(tǒng)自由度增加,進(jìn)而提高了MIMO雷達(dá)的系統(tǒng)性能。其自由度增加雖然帶來(lái)諸多優(yōu)點(diǎn),但是也會(huì)造成雜波協(xié)方差矩陣的維數(shù)增加和獨(dú)立同分布的樣本需求增加。將CS-STAP引入雙基地MIMO模型時(shí),雖然可以降低對(duì)樣本數(shù)的需求,并消除檢測(cè)單元離散雜波點(diǎn)的干擾,但是其計(jì)算量將大大增加,不利于實(shí)現(xiàn)。因而本文針對(duì)這一問(wèn)題提出了一種基于壓縮感知的降維雜波抑制方法,使其既擁有直接數(shù)據(jù)域的壓縮感知方法所具備的樣本數(shù)較少的優(yōu)點(diǎn)外,又改善了其計(jì)算量大的不足。通過(guò)對(duì)結(jié)果的仿真分析,可以證明在性能損失不多和小樣本的情況下,其計(jì)算量將大大減少。
[Abstract]:With the complexity of electromagnetic environment and the improvement of radar performance, multi-input and multi-output (MIMO) radar has attracted more and more attention. Compared with the traditional phased array radar, each element of MIMO radar transmitter transmits orthogonal waveform signals, and the transmitting channel is separated by pulse compression of echo signal at the receiving end, thus increasing the degree of freedom and improving the radar performance. The introduction of MIMO technology into airborne bistatic radar not only has the advantages of the above MIMO radar, but also has the advantages of bistatic detection of stealth targets, covert detection and so on. By processing the echo data of the receiver, the angle information of the transmitter and the receiver relative to the target is obtained, which reduces the requirement of time synchronization of the radar under the traditional configuration. In this paper, the compression sensing (CS) theory, which is a new technology produced in recent years, is applied to MIMO radar, and the clutter suppression of bistatic MIMO radar, the elimination of the influence of unsatisfactory transmission waveform of MIMO radar on the detection performance and the adaptive processing of (STAP) are studied. The main work is as follows: 1. In practice, it is difficult to design orthogonal waveforms with ideal correlation, and the autocorrelation and cross-correlation sidelobe of waveforms are not zero, which will lead to errors in the estimation of clutter covariance matrix, which will have a serious impact on radar performance. In order to solve this problem, this paper first analyzes the causes of the influence of autocorrelation and cross-correlation on Clutter suppression, and then proposes a method of Clutter suppression based on compressed perception. This method not only has good performance in small samples, but also can effectively eliminate the influence of transmitting waveform on clutter suppression. Through the simulation and analysis of the performance of the proposed method, it is verified that the algorithm can effectively eliminate the influence of the unideal transmission waveform on the clutter suppression of MIMO radar. 2, because MIMO radar increases the virtual aperture by transmitting waveform diversity, the degree of freedom of MIMO radar system is increased, and then the system performance of MIMO radar is improved. Although the increase of degree of freedom brings many advantages, it will also lead to the increase of the dimension of the clutter covariance matrix and the increase of the demand for independent and homogeneously distributed samples. When CS-STAP is introduced into the bistatic MIMO model, although the demand for the number of samples can be reduced and the interference of discrete stray points in the detection unit can be eliminated, the amount of computation will be greatly increased, which is not conducive to the implementation. Therefore, in order to solve this problem, a reduced dimension clutter suppression method based on compressed sensing is proposed in this paper, which not only has the advantages of less samples in direct data domain compression sensing method, but also improves the shortage of large amount of computation. Through the simulation analysis of the results, it can be proved that the calculation amount will be greatly reduced when the performance loss is small and the sample is small.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51

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