Azimuth Estimation Using Weighted Correlation Matrices
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Solution Overview
Problem
Existing azimuth estimation methods using correlation matrices face challenges in suppressing cross-correlation components, particularly when using unevenly-spaced antenna arrays or modulation methods like Fast-Chirp Modulation, which limits the accuracy of target separation and estimation.
Innovation Solution
The method involves generating a center matrix from peak bins and surrounding matrices within a preset range, integrating them through weighted addition, and applying time averaging to reduce cross-correlation components, enabling accurate azimuth estimation even with limited snapshots and uneven antenna arrays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spatial averaging is used to suppress cross-correlation components, then azimuth estimation accuracy is improved, but the method can only be applied to evenly spaced antenna arrays which limits adaptability
Solution Approach 1:
The patent applies local quality by making different parts of the antenna array contribute differently to the correlation matrix. Specifically, it uses weighting coefficients that vary across antenna elements to suppress cross-correlation components locally while maintaining the overall array structure, enabling both accuracy improvement and adaptability to unevenly spaced arrays.
Solution Approach 2:
The patent changes parameters by introducing adjustable weighting coefficients and using different window functions to suppress cross-correlation components. This allows the method to adapt to various antenna array configurations including unevenly spaced arrays, while maintaining azimuth estimation accuracy through parameter optimization.
2Measurement precision
If time averaging is used to suppress cross-correlation components, then azimuth separation accuracy is improved, but the method requires multiple snapshots which increases measurement time
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the correlation matrix structure and weighting coefficients before actual measurement. This allows the system to quickly process incoming signals without requiring extensive real-time computation, thereby reducing measurement time while maintaining azimuth separation accuracy through pre-optimized processing.
3Speed
If Fast-Chirp Modulation is used for radar signaling, then target detection speed is improved, but cross-correlation components cannot be suppressed which deteriorates azimuth estimation accuracy
Solution Approach 1:
The patent introduces an intermediary processing step that operates on the correlation matrix derived from Fast-Chirp Modulation signals. By applying weighting coefficients and window functions as intermediaries, the system can suppress cross-correlation components in the frequency domain without changing the time-domain signaling method, thus maintaining both detection speed and azimuth estimation accuracy.
Data Source
AI summary
In an azimuth estimation device, a center generation unit configured to generate, for each peak bin extracted by the extraction unit, a center matrix which is a correlation matrix obtained using values of the same peak bin collected from all of transmitting/receiving channels. A surrounding generation unit is configured to generate, for each of one or more surrounding bins of each of the peak bins, a surrounding matrix which is a correlation matrix obtained using values of the same surrounding bin collected from all of the transmitting/receiving channels. An integration unit is configured to generate, for each peak bin, an integrated matrix which is a correlation matrix obtained by weighting and adding the center matrix and the one or more surrounding matrices. An estimation unit is configured to execute an azimuth estimation calculation using the integrated matrix generated by the integration unit.