Radar Signal Processing with Clustering for False-Target Elimination
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Solution Overview
Problem
Radar systems face challenges in distinguishing between real and false targets due to interference, which can saturate the data processing system and hinder accurate target identification.
Innovation Solution
A signal processing method that involves clustering targets based on azimuth and performing signal-to-noise ratio analysis to identify and eliminate false targets, utilizing a clustering algorithm to group targets by azimuth and applying statistical analysis to remove targets with non-compliant signal-to-noise ratios and false targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar systems perform scanning operations to detect targets, then target detection capability is improved, but false targets and interference increase
Solution Approach 1:
The patent segments the target detection process into multiple stages: initial target acquisition, clustering based on azimuth and other attributes, signal-to-noise ratio analysis, and false target elimination. By dividing the processing into discrete segments with specific functions, the system can effectively distinguish real targets from false targets while maintaining comprehensive detection capability
Solution Approach 2:
The patent implements feedback mechanisms through iterative processing where detection results are analyzed, false targets are identified and eliminated, and the process is repeated with refined parameters. The system uses feedback from signal-to-noise ratio analysis and clustering results to continuously improve target identification accuracy
2Loss of information
If radar systems process all detected targets, then target identification completeness is improved, but data processing system saturation occurs
Solution Approach 1:
The patent extracts and eliminates false targets from the target set through clustering analysis and signal-to-noise ratio filtering. By removing false targets early in the processing chain, the system reduces the burden on subsequent processing stages while maintaining complete analysis of genuine targets
Solution Approach 2:
The patent performs preliminary clustering and false target identification before detailed target analysis. By pre-processing the target data to group similar targets and eliminate obvious false targets, the system prepares the data in advance for more efficient processing in subsequent stages
3Measurement precision
If radar systems use clustering algorithms to group targets, then false target elimination is improved, but processing complexity increases
Solution Approach 1:
The patent applies different processing strategies to different clusters of targets based on their specific characteristics. Rather than using a uniform complex algorithm for all targets, the system adapts the processing approach to local cluster properties, simplifying overall processing while maintaining high false target elimination accuracy
Data Source
AI summary
The present application discloses a signal processing method, device, and storage medium. The signal processing method comprises: acquiring a scanned target collection and multiple initial targets, and dividing them into multiple clusters; performing signal-to-noise ratio statistical analysis and false target statistical analysis on each first cluster among the multiple clusters, thereby removing initial targets with non-compliant signal-to-noise ratio and false targets. The signal processing method is capable of identifying and eliminating initial targets with non-compliant signal-to-noise ratio and false targets.