本文選題：幅相誤差自校正 + MIMO雷達��； 參考：《西安電子科技大學(xué)》2015年碩士論文

【摘要】：近些年來隨著研究的不斷深入,MIMO雷達在目標(biāo)檢測、參數(shù)估計、干擾抑制以及低截獲率等方面的優(yōu)勢逐漸顯現(xiàn)。MIMO雷達在發(fā)射通道和接收通道采用了更多的有源器件,這些器件的幅相特性都會隨加工誤差、工作環(huán)境的變化和使用年限等因素發(fā)生改變。大多數(shù)MIMO雷達信號處理算法都是基于陣列流形已知的情況,但是發(fā)射接收通道的幅相誤差會改變陣列流形,從而嚴重影響算法的性能,因此對幅相誤差校正的研究具有理論意義和實用價值。根據(jù)是否需要設(shè)置校正源,可以將幅相誤差校正方法分為有源校正和自校正兩類。有源校正需要設(shè)置方向已知的校正源,因此應(yīng)用場景受限。本文針對MIMO雷達幅相誤差自校正問題進行了研究,工作的主要內(nèi)容包括如下兩個方面:1.傳統(tǒng)的MIMO雷達幅相誤差自校正迭代算法將幅相誤差和目標(biāo)參數(shù)設(shè)為代價函數(shù)的變量,為了使代價函數(shù)最小化需要在幅相誤差和目標(biāo)參數(shù)間交替迭代求解。但是這類算法存在收斂于局部解的缺陷的問題。同時,當(dāng)幅相誤差較大時,傳統(tǒng)的迭代算法收斂緩慢甚至不收斂。另一方面?zhèn)鹘y(tǒng)的基于輔助陣元的幅相誤差自校正方法雖然不需要迭代,沒有收斂性問題,但是由于其需要對參數(shù)進行多維搜索,計算量大、估計精度低。為了克服以上問題,本文提出了一種改進的基于輔助陣元的MIMO雷達幅相誤差自校正方法。該方法利用三個完全校正的輔助陣元,在MIMO雷達接收數(shù)據(jù)中形成旋轉(zhuǎn)不變因子。通過對協(xié)方差矩陣的奇異值分解獲得目標(biāo)角度的估計,并估計出發(fā)射陣列和接收陣列的陣列流形,進而可以提取出發(fā)射陣列和接收陣列的幅相誤差。仿真分析表明,本文方法不需要迭代和搜索,具有較高的幅相誤差估計精度。2.上述MIMO雷達幅相誤差自校正方法都是基于目標(biāo)參數(shù)和幅相誤差的聯(lián)合求解。由于機載MIMO雷達雜波功率遠遠高于目標(biāo)功率,當(dāng)幅相誤差未知時難以實現(xiàn)目標(biāo)參數(shù)和幅相誤差的聯(lián)合求解。雖然基于壓縮感知的機載雷達幅相誤差校正方法能夠利用雜波求解幅相誤差,但是在幅相誤差較大的情況下無法收斂。針對上述問題,本文提出了一種基于雜波子空間特性的機載MIMO雷達幅相誤差自校正方法。該方法利用扁長橢球波函數(shù)構(gòu)造雜波子空間,結(jié)合最大似然估計方法,獲得了幅相誤差的閉式解。該方法利用機載MIMO雷達的雜波特性,不需要求解目標(biāo)參數(shù),同時不要求雜波在不同距離門間獨立同分布,因此具有較高的實用性。仿真與分析表明,該方法僅需要較少距離門的數(shù)據(jù)即可實現(xiàn)幅相誤差的自校正,并且其性能優(yōu)于基于壓縮感知的算法。
[Abstract]:In recent years, the advantages of MIMO radar in target detection, parameter estimation, interference suppression and low interception rate gradually show that MIMO radar uses more active devices in both transmit and receive channels. The amplitude-phase characteristics of these devices vary with processing error, working environment and service life. Most MIMO radar signal processing algorithms are based on the known array manifold, but the amplitude and phase error of the transmitting and receiving channel will change the array manifold, which will seriously affect the performance of the algorithm. Therefore, the study of amplitude and phase error correction has theoretical significance and practical value. According to whether it is necessary to set up the correction source, the amplitude and phase error correction methods can be divided into two categories: active correction and self correction. The active correction needs to set the correction source with known direction, so the application scene is limited. In this paper, the amplitude and phase error self-tuning problem of MIMO radar is studied. The main contents of the work are as follows: 1. The traditional MIMO radar amplitude-phase error self-tuning iterative algorithm sets the amplitude-phase error and the target parameters as variables of the cost function. In order to minimize the cost function, the iterative solution between the amplitude-phase error and the target parameters is needed. However, this kind of algorithm has the defect of converging to the local solution. At the same time, when the amplitude and phase error is large, the convergence of the traditional iterative algorithm is slow or even non-convergence. On the other hand, the traditional amplitude-phase error self-tuning method based on auxiliary array element does not need iteration and has no convergence problem. In order to overcome the above problems, an improved MIMO radar amplitude and phase error self-tuning method based on auxiliary array elements is proposed in this paper. In this method, three fully corrected auxiliary elements are used to form a rotation invariant factor in the data received by MIMO radar. The target angle is estimated by the singular value decomposition of the covariance matrix, and the array manifolds of the transmit and receiving arrays are estimated, and the amplitude-phase errors of the transmitting and receiving arrays can be extracted. Simulation results show that the proposed method does not need iteration and search, and has a high amplitude and phase error estimation accuracy of .2. The above MIMO radar amplitude-phase error self-tuning methods are based on the joint solution of target parameters and amplitude-phase errors. Because the clutter power of airborne MIMO radar is far higher than the target power, it is difficult to solve the target parameter and the amplitude and phase error when the amplitude and phase error is unknown. Although the amplitude and phase error correction method of airborne radar based on compression sensing can use clutter to solve the amplitude and phase error, it can not converge when the amplitude and phase error is large. In order to solve the above problems, a new method of amplitude and phase error self-tuning for airborne MIMO radar based on clutter subspace characteristics is proposed in this paper. In this method, the clutter subspace is constructed by using the ellipsoidal wave function of flat length and the closed-form solution of the amplitude and phase error is obtained by combining the maximum likelihood estimation method. This method makes use of the clutter characteristics of airborne MIMO radar, and does not need to solve the target parameters, at the same time, it does not require the clutter to be distributed independently among different distance gates, so it has high practicability. Simulation and analysis show that the proposed method can self-correct the amplitude-phase error only with less range gate data, and its performance is better than that based on compression sensing.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN958

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本文編號：1931376