共查询到19条相似文献,搜索用时 187 毫秒
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针对双基地稀疏阵列MIMO雷达目标定位问题,该文提出一种基于投影处理与奇异值分解的多测量矢量欠定系统正则化聚焦求解(Projection-SVD-RMFOCUSS, PSVDRMF)算法.该算法首先估计接收角,接着依次将回波信号向目标存在的角度进行投影,最后将投影后的数据重排进行发射角估计,从而得到目标的准确位置.同时借助奇异值分解(SVD)进行信号降维与能量积累,进一步降低运算量,提高了传统压缩感知恢复算法在低信噪比下的估计性能.与现有稀疏重建算法相比,该算法减少了2维场景带来的庞大运算负担,且保持了良好的性能,可以稳健地对相干与非相干目标进行定位. 相似文献
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一种基于L阵的二维解相干测向算法 总被引:1,自引:0,他引:1
本文对高斯白噪声环境下基于L型阵列二维测向的ESPRIT算法进行了改进.该算法利用阵列结构特点通过平滑原理获得3个互相关矩阵,然后由3个矩阵构造一个特殊大矩阵并对其进行奇异值分解来估计信号子空间,最后利用2D-ESPRIT方法实现二维测向.该算法估计精度高,运算量小,能够对相干信号进行估计. 相似文献
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针对双基地MIMO雷达收发角(DOD-DOA)估计问题,该文提出一种基于联合矩阵对角化的快速多目标收发角估计算法。该算法首先根据匹配滤波输出的数据结构,利用奇异值分解和秩1矩阵判断定理将收发角度估计问题转化为联合矩阵对角化问题,然后采用单次-扫描迭代算法对其求解,得到收发阵列流型矩阵,最后通过谱分析方法估计收发角。该算法充分利用匹配滤波输出的所有信息,无需2维谱峰搜索,每次迭代均可得到精确的闭式解,且收发角自动配对。与现有算法相比,该算法不仅提高了角度估计精度,而且有效降低了运算量。仿真结果证明了所提算法的有效性。 相似文献
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针对传统的二阶统计量角度估计算法在高斯色噪声环境下估计性能急剧下降甚至失效的问题,该文提出一种基于四阶累积量的单基地MIMO雷达相干分布式目标角度估计算法。首先建立单基地MIMO雷达的相干分布式目标信号模型,求取信号的四阶累积量矩阵;利用特征值分解分离出相互正交的信号子空间与噪声子空间,根据多重信号分类(MUSIC)算法原理,获得阵列的空间谱函数,通过谱峰搜索得到分布式目标的中心波达方向。该算法充分利用了四阶累积量对高斯过程的不敏感性,能够很好地抑制高斯色噪声对角度估计的影响。仿真结果证明了该算法的正确性和有效性。 相似文献
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Xiaofei Zhang Hailang Wu Jianfeng Li Dazhuan Xu 《International Journal of Electronics》2013,100(9):1207-1221
In this article, we consider a computationally efficient direction of departure and direction of arrival estimation problem for a bistatic multiple-input multiple-output (MIMO) radar. The computational loads of the propagator method (PM) can be significantly smaller since the PM does not require any eigenvalue decomposition of the cross correlation matrix and singular value decomposition of the received data. An improved PM algorithm is proposed to obtain automatically paired transmit and receive angle estimations in the MIMO radar. The proposed algorithm has very close angle estimation performance to conventional PM, which has a much higher complexity than our algorithm. For high signal-to-noise ratio, the proposed algorithm has very close angle estimation to estimation of signal parameters via rotational invariance technique algorithm. The variance of the estimation error and Cramér–Rao bound of angle estimation are derived. Simulation results verify the usefulness of our algorithm. 相似文献
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在多输入多输出(MIMO)雷达中,针对平滑l0范数(SL0)因感知矩阵的病态性而导致其失效的问题,提出了一种基于截断修正SL0的MIMO雷达目标参数估计方法.该方法在对MIMO雷达感知矩阵进行截断奇异值分解(TSVD)处理的基础上,将保留的奇异值以均值为截断门限,分成较大和较小的两部分,分别采用不同的修正准则进行修正;然后经奇异值分解(SVD)反变换获得非病态感知矩阵,利用该非病态感知矩阵通过SL0算法对MIMO雷达目标参数进行估计,从而显著提高了MIMO雷达目标参数估计的精度和速度.仿真结果验证了该方法的有效性. 相似文献
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针对不相关辨别分析方法在目标类别数较多时计算量大,且可能面临散度矩阵奇异的问题,提出了一种核不相关辨别子空间算法,并将其用于雷达目标一维距离像识别。新算法继承了原方法提取目标统计不相关辨别特征的优点,同时利用核机器学习理论与广义奇异值分解,有效解决了计算量与矩阵奇异的问题,并进一步改善了目标的类可分性。对ISAR实测飞机数据进行了分类,并与几种经典核非线性方法进行了比较,结果表明所提方法的识别性能得到了明显改善。 相似文献
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In this article, we study the problem of four-dimensional angles estimation for bistatic multiple-input multiple-output (MIMO) radar with arbitrary arrays, and propose a joint two-dimensional direction of departure (2D-DOD) and two-dimensional direction of arrival (2D-DOA) estimation algorithm. Our algorithm is to extend the propagator method (PM) for angle estimation in MIMO radar. The proposed algorithm does not require peak searching and eigenvalue decomposition of received signal covariance matrix, because of this, it has low computational complexity. And it can achieve automatic pairing of four-dimensional angles. Furthermore, the proposed algorithm has much better angle estimation performance than interpolated estimation method of signal parameters via rotational invariance techniques (ESPRIT), and has very close angle estimation performance to ESPRIT-like algorithm which has higher computational cost than the proposed algorithm. We also analyze the complexity and angle estimation error of the algorithm, and derive the Cramer‐Rao bound (CRB). The simulation results verify the effectiveness and improvement of the proposed algorithm. 相似文献
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A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramér-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness. 相似文献
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针对目标个数未知时双基地MIMO雷达角度跟踪问题,该文提出一种基于改进自适应非对称联合对角化(AAJD)的目标个数与角度联合跟踪算法。AAJD算法中无法得到特征值变量,因此改进AAJD算法引入主成分顺序估计思想,循环求出特征值,然后运用改进信息论准则估计出目标个数。其次提出目标个数防抖动算法,提高了稳健性。最后改进了ESPRIT算法,完成了目标参数的自动配对和关联。仿真结果表明改进AAJD算法能够成功跟踪目标个数和角度,验证了理论分析的有效性。 相似文献
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This paper discusses the problem of the direction of departure (DOD) and the direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar with array gain-phase errors. In this paper, we propose a propagator method (PM)-like algorithm for joint angle and array gain-phase errors estimation in MIMO radar. The proposed method not only yields automatically paired estimates of the angles and gain-phase errors but also has much better gain-phase errors estimation performance than the estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm; this has higher computational cost than the proposed algorithm. Furthermore, the proposed algorithm has angle estimation performance very close to ESPRIT-like algorithm. We also derive the Cramér–Rao bound (CRB) for MIMO radar with array gain-phase errors. Simulation results present the usefulness of our approach. 相似文献