Projectile Locating Method Based on Improved Gauss-Newton-Genetic Hybrid Algorithm

Abstract

The invention belongs to the technical field of radar signal processing, and discloses a projectile positioning method based on an improved Gauss-Newton-genetic hybrid algorithm. The implementation steps are as follows: first use scene matching to obtain the latitude and longitude of multiple feature points corresponding to the slant distance information in the reference map, construct a nonlinear equation system after coordinate system conversion, and then solve the problem of projectile in imaging by using genetic algorithm and Gauss Newton method The position under the coordinate system further obtains the longitude and latitude of the projectile under the geocentric coordinate system. The invention greatly improves the robustness of solving the nonlinear equation group, can obtain the stable and high-precision projectile position, and can be used for real-time correction of the flight trajectory of the projectile.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a projectile positioning method based on an improved Gauss-Newton-genetic hybrid algorithm, which can be used for projectile positioning in the final guidance stage. Background technique [0002] The missile-borne synthetic aperture radar (SAR) scene matching guidance is used to correct the accumulated error of the inertial guidance. First, the "digital real-time map" obtained by the missile-borne SAR is compared with the "digital reference map" prepared in advance by means of remote sensing and telemetry, and then the generated Guidance commands are used to correct the trajectory deviation and guide the projectile to fly to the target area. [0003] For the scene matching guidance of missile-borne SAR in the final guidance stage, the existing methods can be roughly divided into two categories: methods based on single feature points and methods based o...

AI Technical Summary

Problems solved by technology

The method based on single feature points is easy to calculate, but it relies on accurate image matching and accurate system measurement values. In actual engineering, there will be inevitable errors in both image matching and system measurement values. Single feature point positioning has large parameter errors. The positioning results cannot be effectively corrected in the case of

Although the method based on multiple feature points can correct the positioning error, the commonly used iterative method is very time-consuming and cannot meet the real-time requirements

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