基于假设检验的雷达近邻目标距离统计分辨限——幅度随机分布

Hypothesis Testing Based Range Statistical Resolution Limit of Radar—Random-distributed amplitude

  • 摘要: 基于假设检验的统计分辨研究能够衡量统计意义下的分辨能力,还能够突破瑞利限的限制。当前研究均假定两目标的回波幅度为确定情况,实际中雷达观察的快起伏目标回波服从随机分布。基于随机分布假设,本文推导了两近邻点目标的距离统计分辨性能。研究表明,两种假设下的检验统计量均服从加权卡方分布,统计分辨概率和波形、幅度相关系数、回波信噪比等多种因素有关。仿真验证了理论推导的正确性,并且与应用于时延分辨的MUSIC算法相比,该方法具有更好的距离超分辨性能。

     

    Abstract: The research of Statistical Resolution Limit (SRL) based on hypothesis testing can measure the resolution ability in the statistical point and break through the Rayleigh limit. However, the researches presented have made an assumption that the amplitudes of two signals are determined, while in the reality that of the fast-fluctuating targets are random-distributed. Therefore, we derive the range statistical resolution limit of the two adjacent targets under this assumption. The studies show that both tests under two hypotheses are weighted Chi-Square distributed, and the statistical resolution performance is related to factors, such as the waveforms, the coefficients of the amplitudes and the signal-noise ratio (SNR), etc.. The simulation results demonstrate the correctness of the theoretical results, and this method accesses a much better performance compared with the MUSIC algorithm applied in the range resolution.

     

/

返回文章
返回