谱相关测向新算法及其在TMS320C25上的实现

A New Direction Finding Algorithm Using Spectral Correlation and Its Implement on TMS320C25

许多已调通信信号具有周期平稳性,在时域其自相关函数具有周期性,在频域同期频率具有谱相关特性。利用这种谱相关特性使许多信号处理技术具有了很多有用的新特点。本文介绍了两种测向新算法,它们通过谱相关理论的应用,使新算法具有信号选择性,克服了当今流行的空间谱估计测向算法存在的不足。新算法开发了期望信号已知的谱相关特性,在多径和任意数目、任意接近于期望信号的干扰存在情况下,都能估计出期望信号的到达方向。计算机模拟证实了这一良好性能,并且在TMS320C25系统上实时实现了这种新算法。

Many modulated communication signals exhibit a cyclo-stationary (or periodic correlation) property. In the time domain, its autocorrelation function exhibits periodicity with some period, in the frequency domain, the cycle frequency exhibits its spectral correlation property . By means of this spectral correlation property .many signal processing techniques may be made to gain a lot of useful characteristics. In this paper, two new algorithms are introduced by using the spectral correlation theory. The new algorithms have obtained the signal selectivity and overcome the limitations of existing methods using spatial spectrum estimation. Exploiting the known spectral correlation properties of desired signals, the new algorithms can estimate the directions of arrival of desired signals in the presence of multipath and arbitrary numbers of closely spaced interfering signals. This fine performance is demonstrated with the computer simulation, and these new algorithms have been implemented in real-time on TMS320C25 system.