Information theory based non-circular sparse array DOA estimation performance evaluation method

Abstract

The application discloses a non-circular sparse array DOA estimation performance evaluation method based on information theory, which comprises the following steps: firstly, a multi-dimensional probability density function (PDF) of a received signal is constructed, a joint PDF of the received signal and DOA and a DOA posteriori PDF are derived through information theory, and a system DOA information quantity is obtained by simplifying the DOA posteriori PDF with a Bessel function; then, a DOA posteriori PDF of given noise is derived, and a DOA information approximate upper limit is obtained by simplifying the DOA posteriori PDF with a Taylor expansion; finally, a DOA estimation performance index entropy error is obtained by using the posteriori differential entropy; the application builds a non-circular sparse array system DOA information theory framework based on information theory, in actual signal processing, the entropy error of a parameter can be calculated only by estimating the posteriori PDF of the parameter, and a performance limit independent of an algorithm is provided; in addition, it is found through simulation that the DOA information quantity approaches the DOA information upper limit under a high signal-to-noise ratio, and the entropy error approaches the Cramer-Rao limit, thereby verifying the rationality of the index.

Images