Greedy Target Detection Stop Criterion for Sparse Phased Array Radar
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Solution Overview
Problem
Existing automotive radars with limited angular resolution struggle to detect targets effectively due to their constrained performance, and greedy target detection algorithms face challenges in determining the optimal stop criterion, leading to either under or over-detection of targets.
Innovation Solution
A method for stopping a target detection greedy algorithm in a radar system with a sparse array, involving the addition of a complex DC component to the residue, estimation of noise variance, and hypothesis testing using F-tests to determine when to stop the algorithm, ensuring accurate detection of all targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If greedy target detection algorithms are used with sparse arrays, then target detection capability is improved, but determining the optimal stop criterion becomes difficult leading to under or over-detection
Solution Approach 1:
The patent implements a feedback mechanism where the algorithm continuously monitors the residue signal and compares it against a dynamically calculated threshold based on noise variance estimation. This feedback loop allows the algorithm to automatically determine when to stop iterating, preventing both under-detection and over-detection without requiring complex external control mechanisms.
Solution Approach 2:
The algorithm performs self-assessment by estimating the noise variance from the residue signal itself and using this information to determine its own termination condition. The system serves itself by generating the stopping criterion from its own operational data, eliminating the need for external control complexity.
2Reliability
If more iterations are performed to improve detection accuracy, then detection completeness increases, but processing time and computational load increase
Solution Approach 1:
The patent employs a dynamic stopping criterion that adapts during the iteration process. The threshold for termination is not fixed but evolves based on the estimated noise variance and the characteristics of the residue signal at each iteration stage. This dynamic approach allows the algorithm to stop as soon as sufficient detection completeness is achieved, avoiding unnecessary additional iterations and reducing processing time.
3Ease of operation
If fixed stop criteria are used, then algorithm simplicity is maintained, but detection accuracy deteriorates due to under or over-detection
Solution Approach 1:
The patent changes the parameter used for stopping the algorithm from a fixed value to a dynamically calculated parameter based on noise variance estimation. By transforming the stop criterion from a static threshold to a dynamic one that adapts to the actual signal characteristics, the algorithm maintains its simplicity while significantly improving detection accuracy and preventing under or over-detection.
Data Source
AI summary
Various embodiments relate to a method and system for stopping a target detection greedy algorithm used in a radar system having a sparse array, including: running an iteration of the target detection greedy algorithm on signals received by the sparse array; adding a complex DC component to a residue produced by the target detection greedy algorithm; estimating the variance of the noise in the received signal; testing a first null hypothesis using the estimate of the variance of noise in the received signal and the average of the square magnitude of the complex data of the received signal; and stopping the target detection greedy algorithm when the first null hypothesis test passes.