DOA估计算法评价准则在不同功率入射信号下的修正

Modification of Evaluation Criterion for DOA Estimation Algorithms in Resolving Incident Signals with Different Power

  • 摘要: 针对复杂电磁环境中信号功率对入射信号波达方向(DOA)估计的影响问题进行研究,发现用于DOA估计算法性能分析的经典评价准则对不同功率入射信号存在局限性。针对该问题,首先证明了强信号功率会影响弱信号DOA估计性能,得到强信号功率增加会导致弱信号功率克拉美罗界上升,即弱信号DOA估计的均方根误差增加。然后分析了DOA估计算法的经典评价准则对分辨不同功率入射信号存在的局限性,通过蒙特卡洛实验验证了经典评价准则对分辨不同功率入射信号存在较大误判率,当弱信号信噪比低于5dB时,其误判率大于50%。最后本文提出了DOA估计算法新的评价准则,并仿真证明了新准则较经典准则更适用于分辨弱信号信噪比较低时的不同功率入射信号。所提出的评价准则可为基于空间谱估计的DOA估计算法性能分析提供参考依据。

     

    Abstract: In this paper, the effect of signal power on the DOA estimation of incident signals in complex electromagnetic environment is investigated. It is found that the classic evaluation criterion for performance analysis of DOA estimation algorithms has limitations on incident signals with different power. Thus, this paper first demonstrates that the power of strong signal has influence on the DOA estimation performance of weak signal. The increasing of strong signal power will lead to the rising of Cramer-Rao Lower Bound of weak signal, that is, the increasing of the root mean square error. Then this paper analyzes the limitations of the classic evaluation criterion for DOA estimation algorithms in resolving incident signals with different power. Further Monte Carlo experiment results prove that the classic evaluation criterion has a large misjudgment rate for resolving incident signals with different power. When the signal to noise ratio (SNR) of the weak signal is below 5dB, the misjudgment rate of the classic evaluation criterion is higher than 50%. Finally, this paper proposes a new evaluation criterion for DOA estimation algorithm in resolving incident signals with different power. The simulation results indicate that the proposed criterion has better resolution than the classical criterion in dealing with incident signals with different power when the SNR of the weak signal is low. The evaluation criteria proposed in this paper can provide a reference for the performance analysis of DOA estimation algorithm based on spatial spectrum.

     

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