基于RLS的二次加权相关时延估计算法

针对测向定位中时延估计的问题，提出了一种基于递推最小二乘（Recursive Least Squares，RLS）算法的二次加权相关时延估计方法。该方法在二次相关算法基础上，一方面引入RLS算法，在二次相关前进行自适应滤波，提高系统抗噪能力，且具有较快的收敛速度；另一方面借鉴广义互相关的思路，引入加权函数，并且采用二次加权方式，提高时延估计的性能。仿真结果表明，在低信噪比环境下，基于RLS的二次加权相关时延估计法使谱峰更加尖锐，抑制了噪声的影响，提高了估计的精度。

A quadratic weighted correlation time delay estimation algorithm based on RLS

For the problem of time delay estimation in direction finding and positioning,a quadratic weighted correlation time delay estimation method based on recursive least squares (RLS) algorithm is proposed.Based on the quadratic correlation algorithm,on the one hand,RLS algorithm is introduced to carry out adaptive filtering before quadratic correlation to improve the anti noise ability of the system,and it also has a fast convergence speed.On the other hand,by using the idea of generalized cross-correlation for reference,the weighting function is introduced,and the quadratic weighting method is used to improve the performance of time-delay estimation.The simulation results show that in the environment of low signal-to-noise ratio,the quadratic weighted correlation time delay estimation method based on RLS makes the spectral peak sharper,suppresses the influence of noise and improves the estimation accuracy.