Angle-Doppler Estimation in Heavy Correlated Interference

Nafiseh Shahbazi, H. Amindavar
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Abstract

In this paper, a Prony estimation method on wavelet-transformed space-time signal is proposed with Adaptive Simulated Annealing (ASA) algorithm as a global optimizer. In addition to denoising property of wavelet transformation, the proposed approach appeals to its decor relating nature. Our method improves the performance of radar systems with large array antenna, such as OTH radars in STAP applications. We show that the conglomeration of Prony estimator and ASA algorithm achieve good performance in terms of detection and resolution in comparison with the classical STAP algorithm in the presence of powerful external correlated interference. Moreover, we present how to apply STAP technique to parameter estimation of target in the correlated non-Gaussian interference environments that causes Maximum Likelihood (ML) function be nonlinear with respect to the angle and Doppler. In the following, ASA algorithm is employed for global optimization of all nonlinear functions. Extensive simulations demonstrate that our proposed algorithm outperforms that previously reported estimators with extremely low computational cost.
重相关干扰下的角-多普勒估计
提出了一种以自适应模拟退火(ASA)算法作为全局优化器的小波变换空时信号的proony估计方法。除了小波变换的去噪特性外,该方法还利用了小波变换的装饰特性。我们的方法提高了具有大型阵列天线的雷达系统的性能,例如STAP应用中的OTH雷达。研究表明,在强外部相关干扰下,与经典STAP算法相比,Prony估计器和ASA算法的组合在检测和分辨率方面取得了良好的性能。此外,我们还介绍了如何将STAP技术应用于相关非高斯干扰环境下的目标参数估计,这种环境会导致极大似然函数(ML)在角度和多普勒方面呈非线性。下面使用ASA算法对所有非线性函数进行全局优化。大量的仿真表明,我们提出的算法以极低的计算成本优于先前报道的估计器。
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