An automatic time point selection method for multi-target ISAR imaging

By calculating the waveform entropy of multi-target ISAR imaging, the time reference is automatically selected, and Keystone transform and two-dimensional imaging are performed. This solves the problems of large computational complexity and manual intervention in multi-target ISAR imaging, and achieves efficient multi-target separation and clear imaging.

CN113960597BActive Publication Date: 2025-09-23NANJING VOCATIONAL UNIV OF IND TECH
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Patent Information

Application Number
CN202111230815.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2021-10-22
Publication Date
2025-09-23
Estimated Expiration
2041-10-22

AI Technical Summary

Technical Problem

Existing multi-target ISAR imaging technology has problems in target separation and imaging efficiency, such as high computational complexity, the need for manual intervention, and low imaging efficiency, especially in the presence of strong noise and interference.

Method used

The concept of information entropy is used to calculate the waveform entropy of multiple frames of one-dimensional range images. The moment with the maximum entropy is automatically selected as the imaging benchmark for Keystone transformation and two-dimensional imaging, avoiding multiple transformations and manual intervention and improving calculation efficiency.

Benefits of technology

The automation and efficient separation of multi-target ISAR imaging are realized, the amount of calculation is reduced, and the imaging efficiency and separation effect are improved.

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Abstract

A method for automatically selecting time points for multi-target ISAR imaging includes the following steps: S1: performing pulse compression on a broadband echo sequence for multi-target imaging; S2: performing range image averaging and calculating the waveform entropy of the average range image; S3: taking the time corresponding to the range image with the maximum waveform entropy as the time reference and performing a Keystone transform; S4: performing azimuth compression on the range image sequence to obtain a multi-target range-Doppler two-dimensional image; S5: after target separation on the range-Doppler plane, performing motion compensation and R-D imaging processing on each target to obtain an ISAR image of each target. By calculating the waveform entropy of the average range image, the present invention can automatically select the time point at which the multi-target overlap is minimized, thereby improving computational efficiency. The automatically selected time point exhibits the best separability of target echoes, thereby improving imaging efficiency.
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