Direction Estimator Using Virtual Arrays for Radar Angle Measurement
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Solution Overview
Problem
Current direction-of-arrival estimation methods using maximum likelihood estimation require finer search grids for high accuracy, leading to increased computational complexity and potential deterioration in angle measurement accuracy due to local solution issues.
Innovation Solution
The radar apparatus employs a direction estimator that performs maximum likelihood estimation using virtual receiving arrays, reducing the number of searches by limiting search grids in two-dimensional planes, thereby maintaining accuracy while minimizing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If finer search grids are used for maximum likelihood estimation, then angle measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the two-dimensional angle estimation problem into two separate one-dimensional estimation problems. First, azimuth angles are estimated using a one-dimensional search grid, then elevation angles are estimated using another one-dimensional search grid. This segmentation reduces the total number of search points from N×M in 2D to N+M in 1D, significantly lowering computational complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent transforms the two-dimensional angle estimation problem into sequential one-dimensional problems by introducing a stepwise estimation approach. The first dimension (azimuth) is estimated independently, then the second dimension (elevation) is estimated conditioned on the first, effectively reducing the search space dimensionality and computational burden.
2Measurement precision
If maximum likelihood estimation is performed in two-dimensional planes, then angle measurement accuracy is improved, but the number of searches increases
Solution Approach 1:
The patent divides the two-dimensional search space into two separate one-dimensional search spaces. Instead of performing maximum likelihood estimation over all possible (azimuth, elevation) pairs simultaneously, the method first searches over azimuth angles only, then searches over elevation angles only, reducing the total number of searches from the product of grid sizes to the sum of grid sizes.
Solution Approach 2:
The patent performs preliminary estimation of azimuth angles before estimating elevation angles. By first determining the azimuth component and using it as a basis for the subsequent elevation estimation, the method reduces the search space for the second dimension, thereby reducing the total number of searches required while maintaining accuracy.
Data Source
AI summary
In a direction estimator, a horizontal array maximum likelihood estimator calculates first maximum likelihood values corresponding to NW angles in a first direction by performing a maximum likelihood estimation process on the first direction using signals received by a first virtual linear array and extracts first candidate angles of arrival of incoming waves in the first direction. A vertical array maximum likelihood estimator calculates second maximum likelihood values corresponding to the NW angles in a second direction by performing a maximum likelihood estimation process on the second direction using signals received by a second virtual linear array and extracts second candidate angles of arrival of incoming waves in the second direction. A horizontal/vertical maximum likelihood estimator estimates, using the first and second candidate angles of arrival, angles of arrival of the NW incoming waves in a two-dimensional plane extending in the first and second directions.