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MIMO雷达DOA估计方法分析 总被引:1,自引:0,他引:1
在介绍多输入多输出(MIMO:Multiple-Input Multiple-Output)雷达的信号模型的基础上,给出了一种目标波达方向(DOA:Direction of Arrival)估计方法--多信号分类(MUSIC:Multiple Signal Classification)方法在MIMO雷达系统DOA估计中的应用。与传统相控阵雷达相比,在MIMO雷达系统中该方法可以分辨的信号源数目有较大增加。通过仿真实验,详细分析了在MIMO雷达系统DOA估计中,多种因素对MUSIC方法测角精度的影响。 相似文献
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为了充分利用统计多输入多输出(MIMO)雷达的空间分集能力,研究了长基线(天线间距与目标探测距离可比拟)统计MIMO雷达的检测方法和性能。首先,根据雷达方程给出了长基线统计MIMO雷达探测目标时各信道的信号模型;然后,根据Neyman-Pearson准则推导了长基线统计MIMO雷达的似然比检测器;最后,从检测概率和威力覆盖两个方面对长基线统计MIMO雷达的检测性能进行了仿真分析。仿真结果表明:在一定条件下长基线统计MIMO雷达的检测性能优于短基线(天线间距与目标探测距离相比可忽略不计)统计MIMO雷达。研究结果对统计MIMO雷达的系统设计、天线布置和实际应用等研究具有重要的参考价值。 相似文献
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由于MIMO雷达的多通道特性,使得MIMO雷达各接收天线之间需要进行大量的数据传输。在MIMO雷达中应用双门限检测可以使数据传输量大大降低。本文在单元平均恒虚警检测器的基础上,提出了一种MIMO雷达双门限恒虚警检测器,设计了MIMO雷达双门限恒虚警检测器的结构,将其检测性能和单门限恒虚警检测器进行了对比,分析了MIMO雷达双门限检测器在多目标环境下的检测性能。仿真结果表明在MIMO雷达中应用双门限检测具有结构简单,数据传输量低等特点,在单目标和多目标环境中,双门限恒虚警检测器的检测性能均优于单门限恒虚警检测器。 相似文献
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首先研究了统计多输入多输出(MIMO)雷达对运动目标参数的估计(也称雷达测量),以雷达估计性能为依据设定其工作参数,提出了一种统计MIMO雷达对运动目标跟踪与参数估计相结合的交互式跟踪方法。理论分析表明,所提方法在目标雷达横截面积(RCS)闪烁严重的情况下仍能很好地进行跟踪,并保持很高的跟踪精度;而且论文中所提出的参数估计法可以有效地降低MIMO雷达参数估计的运算复杂度,解决了参数估计中一大难题。仿真实验也验证了该方法的有效性。 相似文献
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对不同类型的目标,分散型多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的最佳检测器结构各异,且通常不便于工程实现.针对此问题,提出了一种易于工程实现的MIMO雷达检测器结构.首先对MIMO雷达和普通单基地雷达的回波信号模型进行分析,指出了MIMO雷达回波和单基地雷达快起伏目标多脉冲回波之间的相似关系.借鉴单基地雷达针对快起伏目标的检测器结构,提出分散型MIMO雷达可以采用类似的包络检波级联累加器的检测器结构形式.就所设计检测器结构对不同空域起伏目标的检测性能进行了研究,给出了检测性能的理论和仿真曲线. 相似文献
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基于EM算法的非高斯噪声参数估计 总被引:1,自引:1,他引:0
EM算法是一种从"不完全数据"中求解模型参数的极大似然估计的方法,在非高斯噪声的参数估计问题中是一种比较优秀的算法。非高斯噪声的参数估计问题的主要困难是充分统计量是不存在的,这意味着从观测空间到估计空间的映射依赖于这里试图估计的参数。在未知噪声概率密度的情况下,EM算法可以更准确地对非高斯噪声参数进行估计,估计方差接近C-R下界。 相似文献
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Time-of-arrival (TOA) and direction-of-arrival (DOA) are key parameters in the impulse radio ultra wideband (IR-UWB) positioning system with a two-antennas receiver. A two-dimensional (2D) multiple signal classification (MUSIC) algorithm, which requires the 2D spectral peak search, can be used to estimate the parameters, but it has much higher computational complexity. This paper proposes a successive MUSIC algorithm for joint TOA and DOA estimation in IR-UWB system to avoid 2D spectral peak search. The proposed algorithm obtains the initial estimate of TOA corresponding to the first antenna via Root-MUSIC, and simplifies the 2D global search into successive one-dimensional searches to achieve the estimation of TOAs in the two antennas. It then estimates the DOA parameters via the difference of the TOAs between the two antennas. The proposed algorithm can get the parameters paired automatically, and has a much lower complexity than 2D-MUSIC algorithm. In addition, we have derived the mean square error of TOA and DOA estimation of the proposed algorithm and the Cramer–Rao bound of TOA and DOA estimation in the paper. The simulation results show that the parameter estimation performance of the proposed algorithm is better than that of Root-MUSIC, and is almost the same as that of 2D-MUSIC algorithm. Moreover, it has much better performance than matrix pencil algorithm, propagator method and estimation of signal parameters via rotational invariance techniques algorithm. 相似文献
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通过估计墙体厚度及介电常数等环境参数来进行补偿成像是近年来穿墙雷达成像研究领域的热点。为解决传统穿墙成像模型中天线需要严格平行于墙体的限制,以及现有的环境参数估计算法计算效率低,稳健性较差的问题,该文建立了一种新的多发多收(MIMO)体制穿墙雷达成像模型以适应阵列与墙体位置关系未知的情况,同时根据该模型下墙体前后沿回波路径模型,提出一种仅依赖于墙体回波时延的环境参数估计算法,稳健性高并且运算复杂度低。时域有限差分(FDTD)仿真数据验证了成像模型和环境参数估计算法的有效性。 相似文献
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This paper discusses the problem of joint direction of arrival (DOA) and Doppler frequency estimation of coherent targets in a monostatic multiple-input multiple-output radar. In the proposed algorithm, we perform a reduced dimension (RD) transformation on the received signal first and then use forward spatial smoothing (FSS) technique to decorrelate the coherence and obtain joint estimation of DOA and Doppler frequency by exploiting the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. The joint estimated parameters of the proposed RD-FSS-ESPRIT are automatically paired. Compared with the conventional FSS-ESPRIT algorithm, our RD-FSS-ESPRIT algorithm has much lower complexity and better estimation performance of both DOA and frequency. The variance of the estimation error and the Cramer–Rao Bound of the DOA and frequency estimation are derived. Simulation results show the effectiveness and improvement of our algorithm. 相似文献
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A novel method for the blind identification of a non-Gaussian time-varying autoregressive model is presented. By approximating the non-Gaussian probability density function of the model driving noise sequence with a Gaussian-mixture density, a pseudo maximum-likelihood estimation algorithm is proposed for model parameter estimation. The real model identification is then converted to a recursive least squares estimation of the model time-varying parameters and an inference of the Gaussian-mixture parameters, so that the entire identification algorithm can be recursively performed. As an important application, the proposed algorithm is applied to the problem of blind equalisation of a time-varying AR communication channel online. Simulation results show that the new blind equalisation algorithm can achieve accurate channel estimation and input symbol recovery 相似文献