Radar Device Azimuth Estimation via Correlation Matrix Averaging
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Solution Overview
Problem
In in-vehicle radar systems, the existing FCM modulation method struggles to accurately separate the azimuths of multiple objects due to the limited number of snapshots, which hinders effective azimuth estimation.
Innovation Solution
The radar device employs a configuration with multiple transmission and reception antennas, using Fast-Chirp Modulation to transmit chirps with varying phase shift keying, generating beat signals, and performing frequency analysis to create correlation matrices for both short and long-distance bins, allowing for averaging and improved azimuth estimation through correlation suppression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the existing FCM modulation method is used, then the radar device can transmit and receive chirp signals, but the number of snapshots is limited which hinders accurate azimuth estimation
Solution Approach 1:
The patent segments the distance spectrum into multiple distance bins, and for each bin, generates separate correlation matrices. This segmentation allows the system to process multiple independent snapshots from different distance ranges, effectively increasing the total number of snapshots available for azimuth estimation without requiring additional transmission cycles.
2Measurement precision
If multiple correlation matrices are generated for different distance bins, then more snapshots are available for azimuth estimation, but the device complexity increases
Solution Approach 1:
The patent merges the azimuth estimation results from multiple distance bins by combining their respective correlation matrices. This merging process consolidates the information from multiple snapshots into a unified azimuth estimation, achieving accurate angle separation while managing processing complexity through systematic combination rather than independent processing of each bin.
Solution Approach 2:
The patent applies correlation suppression selectively to specific distance bins based on their characteristics. Rather than applying uniform processing to all bins, the system performs partial correlation suppression only where needed (excessive action in specific regions), optimizing the balance between azimuth estimation accuracy and processing complexity by avoiding unnecessary operations on all data.
Data Source
AI summary
The radar device includes a transmission section, a reception antenna section, a reception section, a frequency analysis section, a first correlation matrix generation section, and an averaging process section. The transmission section transmits a chirp at cycle periods, the number of the transmitted chirps being a repetition number. The first correlation matrix generation section generates, for the chirps, first correlation matrixes based on complex information on long-distance bins in distance spectra corresponding to respective reception antennas that have received the identical chirp. The averaging process section performs, for the respective long-distance bins, an averaging process for the repetition number of first correlation matrixes generated so as to correspond to the long-distance bins, to generate average correlation matrixes.