Point target movement velocity detection method based on multiple linear moveout scanning, extending and sampling

Abstract

A point target movement velocity detection method based on multiple linear moveout scanning, extending and sampling comprises the following steps: (1) establishing a multiple linear moveout scanning detection device; (2) using each linear detector to detect point targets in an extending and sampling manner; (3) processing Nt groups of image data acquired by each linear detector to obtain sub-pixel images; (4) performing non-uniformity correction and sub-pixel match on two sub-pixel images processed by the two adjacent processed linear detectors, then performing difference computation to complete the background subtraction; (5) performing threshold filtering on difference images processed by the two adjacent processed linear detectors, extracting positive and negative point pairs in the difference images by adopting the neighborhood constraint criterion, so as to complete the target detection and extraction of moving points in once scanning process; (6) marking regions of paired positive and negative points extracted in the step (5) respectively, calculating movement velocity and movement directions of the targets according to the position relation of the marked regions of the positive and negative points; (7) averaging the movement velocity and the movement directions obtained in the step (6) to obtain the velocity and the direction of a detected target.

Description

technical field [0001] The invention belongs to the field of target detection image processing, and relates to a point target moving speed detection method based on multi-line sequence time-difference scanning extended sampling. Background technique [0002] The research on detection technology of weak and small moving targets in complex background has important applications in civil, aerospace and military. Due to the influence of long imaging distance and complex background, the target is dotted in the image, lacks sufficient texture information and shape information, and the signal-to-noise ratio of the target in the image is very low, which greatly increases the difficulty of weak target detection. At present, general-purpose optical imaging detection systems generally use a single detector for detection and imaging. For the acquired images, filter-based methods, wavelet-based methods, and morphological-based methods are used to perform single-frame background suppressio...

AI Technical Summary

Problems solved by technology

This detection system is often affected by the complex background, and cannot reliably extract targets on a single frame image. At the same time, this detection system does not make full use of the target’s motion information in the process of target extraction, and cannot measure the target’s motion speed through one scan. The estimation of the target requires multiple scans and multi-frame trajectory analysis to realize the analysis and calculation of the target motion speed, which reduces the effectiveness of target detection and increases the complexity of detection data analysis and processing.

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