High-speed stealth target detection method based on polynomial hough Fourier transform

Abstract

The invention provides a high-speed stealth target detection method of the polynomial Hough Fourier transform, and aims at solving the problems in distance walk and Doppler expansion in accumulated detection of a high-speed maneuvering stealth target. The detection method comprises that polynomial models of relatively high resolution are established, energy accumulation of a parameter space is realized by the polynomial Hough Fourier transform, polynomial models of higher resolution are established according to a parameter corresponding to the maximal energy value of the parameter space, polynomial Hough Fourier transform of high resolution is then carried out in small areas and so on till the requirement for compensation precision is met, and thus, coherent accumulation detection for the high-speed maneuvering stealth target is realized. The searching train of thought is approached layer by layer via the multiple resolution levels of the polynomial models, accumulation detection for the target is realized by the provided polynomial Hough Fourier transform, and compared with multi-dimension parameter search in a large range in a traditional method, the computational complexity, the memory amount and the complex degree can be substantially decreased, and convenience is provided for engineering.

Description

technical field [0001] The invention belongs to the field of radar signal processing, and is suitable for solving the accumulation and detection problem of hypersonic vehicles, high-speed unmanned aerial vehicles, ballistic missiles, space debris and other high-speed maneuvering stealth targets in adjacent space. Background technique [0002] Since the birth of radar in the 1940s, radar signal processing has continued to develop and evolve. The functions of radar signal processing have become increasingly complex and diverse, and it has become the core subsystem of modern radar. Due to the emergence of a series of new high-threat targets such as near-space hypersonic vehicles, high-speed stealth drones, ballistic missiles, and space debris, the detection environment of modern radars has become extremely harsh. approach poses serious challenges. [0003] At present, the main method of radar signal processing for stealth target detection is to compress the chirp signal first,...

AI Technical Summary

Problems solved by technology

However, the high-speed movement of the target causes the echo signal to move in distance, and the signal cannot be aligned in time. At the same time, the large acceleration causes the phase of the signal to change, and the Doppler expansion phenomenon will appear during accumulation, resulting in ineffective coherent accumulation. The signal-to-noise ratio is improved, thereby reducing the probability of target detection

In response to this problem, a series of methods have been proposed. For example, the methods used to solve distance walking include frequency domain compensation correction method, envelope frequency domain phase compensation method, Keystone transform method, Radon-Fourier transform method, etc., which are used to solve Doppler extension methods include Dechirp method, fractional Fourier transform method, matching Fourier transform method, etc. These methods have solved the problem of coherent accumulation detection of high-speed maneuvering stealth targets in theory to a certain extent, but in the target When the velocity, acceleration, and even jerk are unknown and the transformation range is large, these algorithms will face the problem of a large amount of calculation and cannot meet the real-time requirements due to the need to search for multi-dimensional parameters in a large range. Although the algorithm optimization design, Parallel processing and other methods can increase the calculation speed to a certain extent, but it needs to be improved on the hardware, which increases the complexity of the system

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