Knowledge assisted space-time adaptive processing method integrating generalized symmetrical structure information

The invention provides a knowledge assisted space-time adaptive processing method integrating generalized symmetrical structure information. The knowledge assisted space-time adaptive processing method integrating the generalized symmetrical structure information comprises steps of (1) performing linear transformation through an unitary transformation matrix and transforming an original space-time adaptive processing problem to be in a form which is equivalent to the original space-time adaptive processing problem to enable a covariance matrix of the original space-time adaptive processing problem to be transferred into a real symmetric matrix in the same dimension from a generalized symmetric matrix; (2) obtaining an estimation of the transformed covariance matrix according to sample data; (3) solving an optimal real symmetric estimation of a prior covariance matrix under the minimum Euclidean distance; (4) solving a minimum mean square error estimation through a generalized linear combination and convex combination method in combination with training samples and the prior covariance matrix; (5) obtaining detector forms under part of uniform model and random non-uniform model assumption according to a two-step design and achieving target detection. The knowledge assisted space-time adaptive processing method integrating the generalized symmetrical structure information has the advantages of effectively reducing demanded quantity of the training samples during covariance matrix estimation in the space-time adaptive processing, remarkably improving the detector performances and being simple in achievement.