Method and apparatus for classifying a probe object, storage medium, and electronic device
By acquiring and analyzing radar cross section (RCS) data and track frame data, and combining RCS thresholds and track frame features, accurate classification of the detected objects was achieved, solving the problem of classification accuracy of vehicle-mounted radar under complex road conditions and improving the object tracking performance of the radar system.
CN116148790BActive Publication Date: 2026-04-28FOSS (HANGZHOU) INTELLIGENT TECH CO LTD
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Patent Information
- Application Number
- CN202211566602.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-12-07
- Publication Date
- 2026-04-28
- Estimated Expiration
- 2042-12-07
AI Technical Summary
Technical Problem
In existing technologies, vehicle-mounted radar has low accuracy in classifying detected objects, which can easily lead to misjudgments and false alarms, especially in complex road conditions, affecting the tracking performance of detected objects.
Method used
By acquiring the radar cross section (RCS) data and track frame data of the target object, and combining the RCS threshold and track frame features, the probability value of the target object in the RCS and track frame dimensions is calculated, and its type is comprehensively determined.
Benefits of technology
It improves the classification accuracy of detected objects, avoids the reduction in classification accuracy caused by over-reliance on RCS data, and enhances the object tracking performance of the radar system.
✦ Generated by Eureka AI based on patent content.
Abstract
The application discloses a kind of detection object classification method and device, storage medium and electronic device, the detection object classification method includes: in the case where target detection object is detected from target scene, the target radar reflection cross section (RCS) data and target track box data of target detection object are acquired;According to target RCS data and target RCS threshold corresponding to target detection object, the probability value that target detection object belongs to target type in the dimension of RCS is determined to obtain first probability, and according to track box data and track box feature data, the probability value that target detection object belongs to target type in the dimension of track box is determined to obtain second probability;According to first probability and second probability, target detection object is classified, using the above technical solution, solve the problem such as lower classification accuracy of detection object in related art.
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