相关噪声背景下加权高阶累积量的时延估计方法

时延估计是双基阵被动定位中的重要问题。在非相关噪声干扰下，应用广义互相关法进行时延估计可以取得良好的估计效果，但在相关噪声干扰情况下其估计性能严重下降。使用高阶累积量进行时延估计，可以有效地去除相关高斯噪声的干扰。采用类似广义互相关加权的方法对高阶累积量进行PHAT加权，进一步抑制噪声的影响，提高了高阶累积量法的估计性能。结果表明，在相关噪声背景下加权高阶累积量时延估计效果优于广义互相关法和高阶累积量法。

Estimation of time delay by using weighted high-order cumulant on correlated noise

Time delay estimation is an important problem in passive localization with dual arrays. For uncorrelated noise, time delay estimation performs well with correlation method. However, the performance will decline severely when the signal is corrupted by correlated noise. Time delay estimation using High-order cumulant can eliminate the effect of interference of correlated Gaussian noise. A windowed method called weighted High-order cumulant, is proposed for restraining noise to improve the performance. Simulations indicate that the estimation performance via the proposed method is better than that of the generalized correlation method and the high-order cumulant method.