本文選題：空時(shí)自適應(yīng)處理 + 運(yùn)動(dòng)目標(biāo)檢測(cè)�。� 參考：《西安電子科技大學(xué)》2014年博士論文

【摘要】：機(jī)載雷達(dá)下視工作時(shí)容易受到強(qiáng)地雜波的影響。傳統(tǒng)的一維時(shí)域?yàn)V波和空域?yàn)V波難以有效濾除這些在多普勒域和空域上都擴(kuò)散的雜波�？諘r(shí)自適應(yīng)處理(Space-Time Adaptive Processing,STAP)技術(shù)聯(lián)合了多個(gè)空間通道和相干脈沖進(jìn)行二維自適應(yīng)濾波,能夠在抑制雜波的同時(shí)保證目標(biāo)獲得一定的相干處理增益,是機(jī)載雷達(dá)雜波抑制的一項(xiàng)關(guān)鍵技術(shù)。為了獲得更優(yōu)的STAP處理性能,理論上用于估計(jì)雜波統(tǒng)計(jì)特性的獨(dú)立同分布樣本數(shù)不應(yīng)少于系統(tǒng)自由度的兩倍。但實(shí)際雜波環(huán)境的非均勻性會(huì)導(dǎo)致STAP處理器無法獲取如此之多的獨(dú)立同分布樣本,從而導(dǎo)致STAP的雜波抑制性能嚴(yán)重下降。如何提高STAP在非均勻環(huán)境下的雜波抑制性能是十分重要的問題。多輸入多輸出(Multiple-Input Multiple-Output,MIMO)雷達(dá)是近年來出現(xiàn)的一種新體制雷達(dá),它的每個(gè)天線陣元具有發(fā)射任意波形的能力。與常規(guī)相控陣?yán)走_(dá)相比,MIMO技術(shù)能夠顯著增加系統(tǒng)的自由度,擴(kuò)展陣列虛擬孔徑,提高目標(biāo)參數(shù)估計(jì)精度。隨著系統(tǒng)自由度的增加,常規(guī)參數(shù)估計(jì)方法的運(yùn)算復(fù)雜度會(huì)相應(yīng)地增加,同時(shí)低信噪比、低快拍數(shù)等非理因素會(huì)使參數(shù)估計(jì)精度嚴(yán)重下降。如何在低信噪比、低快拍數(shù)的非理想環(huán)境下提高M(jìn)IMO雷達(dá)參數(shù)估計(jì)精度,同時(shí)降低運(yùn)算量是值得研究的問題。本論文圍繞這上述問題開展研究,具體包括以下幾個(gè)方面。一、研究了機(jī)載非正側(cè)面陣?yán)走_(dá)距離非平穩(wěn)雜波抑制的問題。當(dāng)機(jī)載雷達(dá)的天線非正側(cè)視安裝時(shí),其雜波譜會(huì)隨著距離的變化而變化,從而導(dǎo)致雜波出現(xiàn)距離非平穩(wěn)的現(xiàn)象。雜波的距離非平穩(wěn)性會(huì)導(dǎo)致傳統(tǒng)STAP無法獲取獨(dú)立同分布的訓(xùn)練樣本。在高重頻工作模式下情況將變得更加復(fù)雜,近程雜波和遠(yuǎn)程雜波由于距離模糊耦合在一起,雜波抑制變得更加困難。提出了一種基于正交波形的俯仰自適應(yīng)波束形成算法用來抑制距離非平穩(wěn)的近程雜波,而剩余的距離平穩(wěn)的遠(yuǎn)程雜波由方位-多普勒STAP來抑制。所提俯仰波束形成算法能夠有效地抑制近程雜波,同時(shí)可以保護(hù)遠(yuǎn)程目標(biāo)。在濾除了距離非平穩(wěn)的近程雜波后,雜波樣本的距離平穩(wěn)性得到明顯的增強(qiáng),能夠?yàn)楹罄m(xù)方位-多普勒STAP處理器提供獨(dú)立同分布的訓(xùn)練樣本,使其雜波抑制性能得到明顯的改善。二、研究了非均勻環(huán)境下采用直接數(shù)據(jù)域STAP方法進(jìn)行雜波抑制的問題。雜波功率上的非均勻會(huì)導(dǎo)致雜波抑制不夠充分或者凹口過深,而離散雜波則容易導(dǎo)致虛警,密集動(dòng)目標(biāo)環(huán)境則容易引起STAP自適應(yīng)方向圖畸變和目標(biāo)自相消。理論上直接數(shù)據(jù)域方法能夠解決上述雜波非均勻的問題。但傳統(tǒng)的直接數(shù)據(jù)域方法存在空時(shí)孔徑損失和受陣列結(jié)構(gòu)限制等問題,提出了一種基于迭代自適應(yīng)譜估計(jì)算法的直接數(shù)據(jù)域STAP方法。該方法能有效避開傳統(tǒng)統(tǒng)計(jì)類STAP算法在非均勻環(huán)境下所面臨的樣本數(shù)不足和樣本污染的難題,且無空時(shí)孔徑損失,適用于任意形狀的陣列。三、研究了機(jī)載雷達(dá)在密集欺騙式干擾環(huán)境下的雜波抑制問題(密集欺騙式干擾環(huán)境可看作是非均勻環(huán)境的一種特殊情況)。機(jī)載雷達(dá)欺騙式旁瓣干擾容易引起大量虛警,使雷達(dá)跟蹤數(shù)據(jù)處理器飽和。而欺騙式主瓣干擾不僅會(huì)引起大量虛警,還會(huì)污染空時(shí)自適應(yīng)處理器的訓(xùn)練樣本,引起自適應(yīng)方向圖畸變,導(dǎo)致期望信號(hào)相消和雜波抑制性能下降。利用目標(biāo)信號(hào)與欺騙式干擾信號(hào)極化特性或者空間達(dá)到角的差異,提出了一種極化-空域聯(lián)合自適應(yīng)波束形成算法來抑制欺騙式主瓣或旁瓣干擾。在增加了極化輔助通道的基礎(chǔ)上,首先采用重疊滑窗的子陣合成方式進(jìn)行極化-空域聯(lián)合自適應(yīng)波束形成,然后通過STAP抑制剩余的雜波。該方法可以有效地濾除密集欺騙式干擾,減少由其引起的虛警,減輕后續(xù)雷達(dá)數(shù)據(jù)處理器的負(fù)擔(dān),改善機(jī)載STAP雷達(dá)的雜波抑制性能。四、研究了機(jī)載前視陣?yán)走_(dá)檢測(cè)近距離地面運(yùn)動(dòng)目標(biāo)時(shí)的雜波抑制問題。機(jī)載前視陣?yán)走_(dá)的近程雜波具有很強(qiáng)的距離非平穩(wěn)性,易使STAP的雜波抑制性能下降。在采用中脈沖重復(fù)頻率探測(cè)近距離運(yùn)動(dòng)目標(biāo)時(shí),模糊的遠(yuǎn)程雜波會(huì)帶來額外的盲速。基于譜補(bǔ)償?shù)腟TAP算法可以用來對(duì)付距離非平穩(wěn)的近程雜波,但它們忽略了模糊的遠(yuǎn)程雜波的影響。提出了一種高效的基于波束空間的俯仰預(yù)濾波算法來濾除遠(yuǎn)程雜波,從而消除遠(yuǎn)程雜波對(duì)目標(biāo)檢測(cè)的影響。所提俯仰波束形成算法不僅具有很好的遠(yuǎn)程雜波抑制性能,還具有保護(hù)近程目標(biāo)信號(hào)不受損失的優(yōu)點(diǎn)。該算法不僅能夠有效消除由遠(yuǎn)程雜波帶來的額外盲速,還能夠改善后續(xù)STAP的雜波抑制性能。另外,所提基于波束空間的降維自適應(yīng)波束形成算法不僅能夠加快收斂速度,還能夠降低運(yùn)算量,有利于工程實(shí)時(shí)實(shí)現(xiàn)。五、研究了單基地MIMO雷達(dá)目標(biāo)波達(dá)方向(Direction of Arrival,DOA)估計(jì)的問題。在低信噪比、低快拍數(shù)的情況下,常規(guī)DOA估計(jì)算法的性能會(huì)嚴(yán)重下降。針對(duì)此問題,提出了一種新的DOA估計(jì)算法:降維酉ESPRIT算法。該算法首先通過降維變換將MIMO雷達(dá)數(shù)據(jù)變換至低維信號(hào)空間,然后在該低維信號(hào)空間構(gòu)造實(shí)值旋轉(zhuǎn)不變性方程估計(jì)目標(biāo)的DOA。該方法能夠在低信噪比、低快拍數(shù)的惡劣環(huán)境下獲得較常規(guī)ESPRIT方法更高的DOA估計(jì)精度,同時(shí)具有更低的運(yùn)算量。
[Abstract]:Airborne radar as the work is easily affected by the strong ground clutter. Time domain filtering and spatial filtering to effectively filter the traditional diffusion in Doppler domain and spatial clutter. Space time adaptive processing (Space-Time Adaptive, Processing, STAP) technology combined with a number of spatial channels and coherent pulse two-dimensional adaptive filtering at the same time, can restrain the clutter target to ensure coherent processing gain of airborne radar clutter suppression is a key technology. In order to obtain STAP better performance, the theory is used to estimate the statistical characteristics of clutter i.i.d. samples should not be less than two times the number of degrees of freedom but the actual system. Clutter heterogeneity will lead to the STAP processor can not get so many i.i.d. samples, resulting in STAP clutter suppression performance severely. How to improve the STAP in Non uniform clutter suppression performance of environment is a very important problem. Multiple input multiple output (Multiple-Input Multiple-Output MIMO) radar is a new radar system in recent years, it has the capability to launch each antenna element of arbitrary waveform. Compared with the conventional phased array radar, MIMO technology can significantly increase the system freedom, virtual aperture extension of the array, the goal of improving the precision of parameter estimation. With the increase of the degree of freedom of the system, conventional parameter estimation methods, the computational complexity will be increased at the same time, low SNR, low number of snapshots and other non physical factors would cause a serious decline in the parameter estimation accuracy. In low SNR, improve MIMO radar parameter estimation accuracy of non ideal low number of snapshots, and reduce the amount of calculation is a problem worthy of study. This thesis focuses on the above problems, including the following, Study on airborne sidelooking radar non distance nonstationary clutter suppression for airborne radar antenna. When the non sidelooking installation, the clutter spectrum will change with the change in distance, which leads to the clutter from the non-stationary clutter phenomenon. The distance of non stationarity will lead to the traditional STAP cannot get independent with the distribution of training samples. In high repetition rate mode, the situation will become more complex, short-range clutter and remote clutter due to the distance of fuzzy coupling together, clutter suppression becomes more difficult. This paper proposes a pitch adaptive beamforming algorithm based on orthogonal waveform distance used to suppress the non-stationary short-range clutter, and remote the remaining distance stationary clutter range by Doppler STAP to suppress. The pitch beamforming algorithm can effectively suppress the short-range clutter, and can protect the remote target. In the distance filter Non stationary short-range clutter, clutter sample distance stability was increased, for subsequent range - Doppler STAP processor provides independent and identically distributed training samples, the clutter suppression performance can be improved significantly. Two, studied the non-uniform environment using direct data domain method for problem STAP clutter suppression. The clutter power will lead to the non-uniform clutter suppression is not sufficient or notch too deep, while the discrete clutter can easily lead to false alarm, dense moving target environment is likely to cause STAP adaptive pattern distortion and target self cancellation. The direct data domain method to solve the homogeneous clutter the problem. But the direct data domain method of traditional space-time aperture loss and array structure limitation, puts forward an iterative adaptive spectral estimation algorithm of the direct data domain STAP method based on this method. The problem can effectively avoid the traditional statistical STAP algorithm in the face of non-uniform environment samples and sample the lack of pollution, and no loss of aperture of space-time array for arbitrary shape. Three, clutter suppression of airborne radar in dense deception jamming environment (dense deception jamming environment as a special case of non-uniform environment). Deception sidelobe interference of airborne radar can cause a large number of false alarm, the radar tracking data processor and saturation. The deceptive mainlobe jamming not only causes a large amount of false alarms, but also pollute the space-time adaptive processor of the training sample, caused by adaptive pattern distortion, leading to the desired signal cancellation and clutter suppression performance decreased. The difference reached angle by using the target signal and deception interference signal polarization or space, presents a polarization space adaptive beamforming The algorithm for suppressing the deceptive mainlobe and sidelobe interference. In increasing the basic polarization of the auxiliary channel, first using the overlapping sliding window of sub array synthesis of polarization space adaptive beamforming, and then through the STAP to suppress the residual clutter. This method can effectively suppress the dense deceptive jamming, reduce false alarm by the radar data processor, reduce the follow-up burden, improve the performance of clutter suppression for airborne STAP radar. Four, the research of airborne phased array radar detection of near ground moving target when the clutter suppression for airborne phased array radar. The short-range clutter has strong distance nonstationarity, easy to STAP the performance of clutter suppression is decreased. In the pulse repetition frequency detection near the moving object, fuzzy remote clutter will bring additional blind speed. STAP spectrum compensation algorithm can be used to deal with the non distance based on Smooth the short-range clutter, but they ignore the fuzzy remote clutter. This paper presents an efficient pitch filtering algorithm based on beam space distance to filter out clutter, thus eliminating the remote effect of clutter target detection. The proposed beamforming algorithm not only has the pitch remote good clutter suppression the performance, also has the advantages of protecting the short-range target signal without loss. The algorithm not only can effectively eliminate clutter by remote additional blind speed wave, can also improve the performance of clutter suppression following STAP. In addition, the proposed adaptive beamforming algorithm can not only accelerate the convergence speed of dimension reduction based on beam space, but also can reduce the amount of computation to realize in engineering. In five, the monostatic MIMO radar target DOA (Direction of Arrival, DOA) estimation problem. In low SNR, low sampling number under the condition of conventional DOA The performance of the estimation algorithm will decrease seriously. To solve this problem, we propose a new DOA estimation algorithm: dimensionality reduction unitary ESPRIT algorithm. The algorithm firstly reduced dimensional transformation of MIMO radar data is transformed into a low dimensional signal space, then this method can estimate the target DOA. in the low SNR in the low dimensional signal the space structure of real valued rotation invariance equation, compared with the conventional ESPRIT method DOA higher estimation accuracy for low number of snapshots in the harsh environment, and has lower computation.

【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51

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