Angle-measurement-only target tracking method based on pseudo-linear maximum correlation entropy Kalman filtering

The invention discloses an angle-measurement-only target tracking method based on pseudo-linear maximum correlation entropy Kalman filtering, and the method comprises the following steps: S1, initializing a noise variance and a state transition matrix, and initializing a target initial position state selection Gaussian kernel width sigma and a convergence judgment coefficient epsilon t; s2, linearizing the angle-only observation equation by using a pseudo-linear method, calculating a priori estimated value and a priori covariance matrix Pkk-1 of the target to be tracked, updating a posteriori estimated value according to a maximum correlation entropy unfixed point iterative formula to calculate the deviation of pseudo-linear Kalman filtering, and instantaneously compensating the posteriori estimated value; and S3, when the updating of the posterior estimation value meets the judgment coefficient epsilon t, stopping updating, calculating a posterior covariance matrix, and starting a next round of iteration. Ac