4D Radar Beamforming Using Interference-Orthogonal Subspace Projection
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Solution Overview
Problem
Current radar systems for automotive applications face high computational costs and inefficiencies in estimating angles for multiple targets due to the need to estimate noise and interference power, especially when determining both azimuth and elevation angles simultaneously.
Innovation Solution
The implementation of a 2D radar system with a 2D array of antenna elements that determines first angles without estimating noise or interference power, using a subspace projection matrix to calculate an interference-orthogonal subspace projection-based beamformer, which allows for efficient estimation of desired signal outputs and corresponding second angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adaptive beamforming techniques are used to increase signal strength and suppress interference, then measurement precision is improved, but device complexity increases due to high computational cost
Solution Approach 1:
The patent segments the angle estimation process into two distinct stages: first estimating azimuth angles using a computationally efficient 1D beamformer, then estimating elevation angles using the azimuth results as input. This segmentation avoids the need for complex 2D beamforming while achieving comparable accuracy, thereby reducing computational complexity without sacrificing measurement precision.
2Measurement precision
If 2D array processing is used to achieve high angular resolution, then measurement precision is improved, but device complexity increases due to expensive computer hardware requirements
Solution Approach 1:
The patent divides the 2D angle estimation problem into sequential 1D estimation tasks. By first processing the azimuth dimension and then the elevation dimension using the results from the first stage, the system achieves high angular resolution comparable to full 2D processing but with significantly reduced hardware requirements and computational burden.
Solution Approach 2:
The patent transforms the complex 2D angle estimation problem into a sequence of 1D estimation problems. By processing one dimension at a time (azimuth first, then elevation) and using the results from the first dimension as input to the second, the system achieves equivalent performance to 2D processing with reduced computational complexity and hardware cost.
3Measurement precision
If noise and interference power estimation is performed for each target, then measurement precision is improved, but productivity decreases due to computational inefficiency
Solution Approach 1:
The patent segments the processing workflow to perform noise and interference power estimation only once at the beginning, before target-specific angle estimation. This approach maintains measurement precision by ensuring accurate noise characterization for each target while significantly improving productivity by avoiding redundant computations across multiple targets.
Data Source
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AI summary
This document describes techniques and systems of multiple-target, simultaneous beamforming for four-dimensional (4D) radar systems for efficient angle estimation in two dimensions with a high dynamic range. For example, a processor can use electromagnetic (EM) energy received by a two-dimensional (2D) array to determine first angles in a first dimension associated with one or more objects. The processor can then determine a subspace projection matrix using the first angles without an estimate of the power of noise or interference signals in the received EM energy. Using the subspace projection matrix, the processor can determine an interference-orthogonal subspace projection-based beamformer. With the interference-orthogonal subspace projection-based beamformer, the processor can determine the desired signal output from an adaptive beamformer for the EM energy and second angles corresponding to respective first angles for the objects.