Radar False Detection Removal via CIT Beam Pattern Similarity
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Solution Overview
Problem
Radar systems face false detections due to external interference and clutter, leading to excessive false tracks and missed tracks, particularly in High Frequency Surface Wave Radar (HFSWR) systems where co-channel interference and ionospheric clutter cause directionality issues.
Innovation Solution
A method involving a detection validator that performs similarity measures on adjacent and neighbor coherent integration time values (CITs) to identify and discard false detections by comparing beam patterns across consecutive and neighboring time intervals, utilizing a constant false alarm rate (CFAR) processor to differentiate between real targets and noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the radar operates in a frequency band shared with other users, then the radar can utilize available spectrum resources, but co-channel interference from nearby and far ranges increases false detections
Solution Approach 1:
The patent introduces an intermediary validation process between the CFAR detector and the final track generation. This intermediary step compares beam patterns across adjacent and neighbor CITs to identify and remove false detections caused by co-channel interference, while preserving legitimate targets. The validation mechanism acts as a mediator that filters out interference without blocking legitimate signals.
2Measurement precision
If the radar detection threshold is lowered to capture small targets, then detection sensitivity improves, but false alarms from interference increase
Solution Approach 1:
The patent applies preliminary validation action by comparing beam patterns across adjacent and neighbor CITs before finalizing detections. This preliminary check identifies false alarms generated by interference at the detection stage, allowing the system to maintain low detection thresholds for high sensitivity while filtering out false positives through the validation process.
3Productivity
If the radar processes detections from multiple CITs, then the system can track targets over time, but computational complexity increases
Solution Approach 1:
The patent segments the validation process into distinct components: detecting beam patterns for adjacent CITs, detecting beam patterns for neighbor CITs, computing similarity measures, and making validation decisions. This segmentation allows the complex task of multi-CIT validation to be broken down into manageable steps that can be processed efficiently, maintaining tracking capability while controlling computational complexity.
Data Source
AI summary
In one aspect, a method to identify and remove a false detection includes receiving a detection from a constant false alarm rate (CFAR) processor, performing a first similarity measure on adjacent coherent integration time values (CITs) corresponding to the detection, performing a second similarity measure on neighbor CITs corresponding to the detection, determining if at least one of the first or second similarity measure is below a threshold and discarding the detection if at least one of the first or second similarity measures is below the threshold.