Radar Target Separation Using Iterative Signal Subtraction
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Solution Overview
Problem
Radar systems face limitations in angular separability, contrast ratio, accuracy, and the presence of ghost targets due to conventional processing chains.
Innovation Solution
A radar system with an enhanced processing chain that iteratively detects targets by subtracting the strongest target's signal contribution, jointly optimizes parameters, and refines detections to eliminate ghost targets and improve contrast ratio and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional radar processing chains are used, then the system is simple to implement, but angular separability and contrast ratio are limited
Solution Approach 1:
The radar processing chain is segmented into multiple iterative detection passes. Each pass detects targets above a threshold, estimates their parameters, subtracts their signals from the antenna responses, and updates the residual. This segmentation allows the system to progressively resolve closely spaced targets that would be indistinguishable in a single conventional detection pass, thereby improving angular separability.
Solution Approach 2:
The system performs preliminary detection of strong targets before attempting to detect weaker targets. By first identifying and subtracting the strongest targets from the antenna responses, the system prepares the residual signal to reveal weaker targets that would otherwise be masked. This preliminary action enables the detection of targets with lower contrast ratios.
2Measurement precision
If conventional radar processing is used, then computational resources are conserved, but detection accuracy and ghost target elimination are compromised
Solution Approach 1:
The system performs a limited number of iterative detection passes (e.g., 2-5 iterations) rather than continuing until all possible targets are detected. Each iteration improves detection accuracy by removing stronger targets and revealing weaker ones, but the process is terminated after a predefined number of iterations to control computational energy consumption. This partial action provides a practical balance between accuracy improvement and energy expenditure.
3Reliability
If signal subtraction is performed without joint optimization, then processing is faster, but residual errors create ghost targets
Solution Approach 1:
The system implements feedback by jointly optimizing the parameters of all detected targets in each iteration. After detecting targets and subtracting their signals, the system updates the parameter estimates of all targets based on the residual signal and re-performs subtraction with improved parameters. This feedback loop reduces residual errors that would otherwise create ghost targets, improving reliability.
4Measurement precision
If multiple targets are detected simultaneously, then processing is simpler, but angular separability of closely spaced targets deteriorates
Solution Approach 1:
The detection algorithm is segmented into multiple passes where each pass focuses on detecting targets above a certain threshold. By iteratively detecting, subtracting, and updating, the algorithm effectively segments the detection process into manageable stages, allowing closely spaced targets to be resolved in different passes rather than requiring complex simultaneous multi-target detection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances angular separability, improves detection accuracy, and reduces ghost targets by refining detections through iterative signal subtraction and joint parameter optimization.
Implementation Method 1
The transmitter is configured to transmit radio signals. The receiver is configured to receive a reflected radio signal. The reflected radio signal is the transmitted radio signal(s) reflected from an object or multiple objects in an environment.
Data Source
AI summary
A radar system with enhanced processing for increased contrast ratio, improved angular separability and accuracy, and elimination of ghost targets. The radar system is equipped with transmitters, receivers, pluralities of transmit antennas, and pluralities of receive antennas. The enhanced processing chain on-board the radar system iteratively detects target(s) by first finding the strongest target, subtracting the estimated received signal from the detected target, and repeating the process for subsequent targets until a predefined number of iterations is completed or an exit condition is tripped. The enhanced processing chain's subtraction increases the contrast ratio of detectable targets. The detection is thus refined by determining optimal azimuth, elevation, gain, and phase of each detection through a joint optimization of all detections. The subtraction and refinement aid in eliminating ghost targets by removing sidelobe signals and residual errors that cause ghost targets to appear.