Segmented Radar Presence Detection With Range-Zone Angle Estimation
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Solution Overview
Problem
Existing radar systems face challenges in accurately detecting targets with minimal computational complexity and avoiding false positives, particularly in environments with varying target densities and movements.
Innovation Solution
The use of non-overlapping sine filters to generate range-slow-time data, followed by angle estimation using synthetic antennas, and an occupancy grid map update, which determines target presence probabilities in range and angle zones, minimizing computational complexity and enhancing detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional radar target detection methods (range FFT, Doppler FFT, MTI filtering, digital beamforming) are used, then target detection capability is achieved, but computational complexity increases
Solution Approach 1:
The patent divides the detection process into two segments: a first stage using simplified processing (range FFT only) to identify candidate range zones, and a second stage applying full processing (Doppler FFT, MTI filtering, digital beamforming) only to those candidate zones. This segmentation reduces overall computational complexity while maintaining detection accuracy by avoiding unnecessary processing in zones without targets.
Solution Approach 2:
The patent applies different processing qualities to different spatial regions: full-resolution processing is applied only to range zones where targets are detected, while other zones receive simplified or no processing. This local quality approach ensures high detection accuracy where needed while reducing computational burden in regions without targets.
2Measurement precision
If traditional radar target detection methods are used, then target detection is performed, but false positives increase in environments with varying target densities
Solution Approach 1:
The patent performs preliminary range FFT processing on all range zones before applying more complex detection algorithms. This preliminary action identifies candidate zones that are likely to contain targets, allowing subsequent detection algorithms to focus only on these zones and avoid false positives in zones without targets.
Solution Approach 2:
The patent uses the results from range FFT processing as feedback to guide the application of Doppler FFT, MTI filtering, and digital beamforming. Only range zones showing potential targets in the preliminary stage trigger further processing, creating a feedback loop that reduces false positives by avoiding processing in zones without actual targets.
3Measurement precision
If full processing is applied to all range zones, then detection accuracy is maintained, but processing time increases
Solution Approach 1:
The patent segments the processing pipeline into a fast preliminary stage (range FFT) and a slower detailed stage (Doppler FFT, MTI filtering, digital beamforming). By applying the detailed stage only to candidate zones identified in the preliminary stage, the patent significantly reduces total processing time while maintaining detection accuracy for actual targets.
Solution Approach 2:
The patent applies partial processing (range FFT only) to all range zones, and full processing only to a subset of candidate zones. This partial action approach is sufficient to achieve the detection goal while minimizing processing time by avoiding excessive computation in zones without targets.
Data Source
AI summary
In an embodiment, a method includes: receiving radar digital data; processing the radar digital data with a plurality of sine filters to generate a respective plurality of range-slow-time data, where each sine filter is associated with a respective range zone of a plurality of range zones; generating a first presence score based on a first range-slow-time data of the plurality of range-slow-time data, where the first range-slow-time data is associated with the first range zone; and when the first presence score is higher than a predetermined threshold, generating a plurality of synthetic antennas based on the first range-slow-time data, performing angle estimation based on the plurality of synthetic antennas to generate first probability values for a plurality of angle zones associated with the first range zone, and updating an occupancy grid map based on the first probability values.