Radar Moving Target Detector Clutter Adaptation
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Solution Overview
Problem
Conventional Moving Target Detectors (MTDs) face challenges in effectively distinguishing moving targets from clutter and noise, particularly due to information loss in binary integration, which results in processing gain loss and reduced radar coverage.
Innovation Solution
The implementation of a Moving Target Detector that uses a switching logic module to select between a land-clutter path and a no-land-clutter path based on clutter information, employing a video integrator instead of a binary integrator to process Doppler filter outputs, and utilizing dynamic and clear day clutter maps to adaptively choose between Doppler filter banks, thereby enhancing processing gain and sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a binary integrator is used to process detection results from CFAR detectors, then false alarms are controlled, but information loss occurs resulting in processing gain loss
Solution Approach 1:
The patent inverts the conventional processing sequence by applying integration before detection rather than detection before integration. Specifically, complex Doppler filter outputs are integrated across multiple CPIs to produce integrated complex data, which then feeds into CFAR detectors. This inversion preserves amplitude and phase information throughout the integration process, eliminating the information loss that occurs when binary integration is applied after detection.
Solution Approach 2:
The patent performs preliminary integration of the complex Doppler outputs before the detection stage. By integrating the complex data (maintaining full information content) before applying CFAR detection, the system prepares the data in an optimal state for subsequent detection, thereby maximizing processing gain while maintaining reliable false alarm control through the later CFAR stage.
2Measurement precision
If a video integrator is used instead of a binary integrator, then processing gain and sensitivity are improved, but system complexity increases
Solution Approach 1:
The patent replaces the mechanical/logical binary integration process with a mathematical video integration process operating on complex data. Instead of integrating binary detection results (0 or 1), the system integrates the complex Doppler filter outputs, which preserves amplitude and phase information. This substitution enables continuous-valued integration that provides processing gain and improved sensitivity while managing complexity through efficient complex arithmetic operations.
3Adaptability or versatility
If clutter maps are used to adaptively select Doppler filter banks, then target detection in cluttered environments is improved, but computational load increases
Solution Approach 1:
The patent performs preliminary construction of clutter maps using historical radar data before the adaptive filter selection process. These pre-computed clutter maps characterize the clutter environment across different range and azimuth cells. During operation, the system queries these pre-computed maps to determine appropriate Doppler filter bank selections, avoiding the need for real-time clutter analysis and reducing computational load while maintaining adaptability.
Solution Approach 2:
The clutter maps are built and updated using the radar system's own historical data, allowing the system to self-characterize its operating environment. The adaptive filter selection uses these self-generated clutter maps to automatically adjust processing parameters, eliminating the need for external clutter characterization or manual configuration, thereby reducing computational requirements while maintaining high adaptability.
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
This approach increases radar coverage and sensitivity by up to 1.5 dB on average while maintaining the benefits of conventional MTDs, effectively addressing information loss and improving target detection in cluttered environments.
Implementation Method 1
One option for detecting moving targets in the midst of large clutter is to take advantage of the different Doppler shifts between the targets and clutter
Data Source
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AI summary
Various embodiments are described herein for a moving target detector that processes input data to perform detection for a current range cell. The moving target detector includes a Doppler filter bank module for processing the input data to provide several Doppler outputs for the current range cell, a no-land-clutter path for processing several input data sets related to the several Doppler outputs to provide detection data by performing peak selection on each of the several input data sets and performing detection on the results of the peak selection, a land-clutter path for processing the several input data sets to provide detection data by performing Constant False Alarm Rate (CFAR) detection on each of the several input data sets and merging the detection results; and a switching logic module for selecting one of the land-clutter path and the no-land-clutter path based on clutter information.