Radar Target Confidence Index for Ghost Target Filtering
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Solution Overview
Problem
Existing radar systems often detect 'ghost targets' or false reflections, which are not reliably differentiated from real targets, leading to unreliable target detection.
Innovation Solution
A method and system that calculates a reliable confidence index for radar targets by determining digital data from the environment, assessing false target probabilities, and integrating data from high-definition maps and other sensors to enhance target detection reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar waves are used to detect targets, then detection range and ability to detect hidden targets are improved, but false targets are generated due to stray reflections
Solution Approach 1:
The patent introduces an intermediary processing system that receives raw radar data and processes it through multiple stages: initial filtering to remove obvious false targets, probability calculation based on environmental context, and confidence index computation. This intermediary layer between the radar sensor and the final detection output effectively reduces false targets while preserving real target detections.
Solution Approach 2:
The system implements feedback mechanisms where detection results are continuously evaluated and used to adjust subsequent detection processes. The confidence index calculation incorporates feedback from environmental data and previous detection patterns, allowing the system to dynamically adjust its sensitivity and reduce false targets based on learned patterns and contextual information.
2Measurement precision
If environmental data and sensor fusion are integrated, then false target differentiation is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex data processing task into distinct modular stages: environmental data acquisition, probability calculation module, confidence index computation, and final target identification. Each module handles a specific aspect of the processing, making the overall complex system manageable and maintainable while achieving high measurement precision through the coordinated operation of these specialized components.
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
The method effectively distinguishes between false and real targets by improving the confidence index through environmental mapping and sensor fusion, enhancing the reliability of radar target detection.
Implementation Method 1
a radar, in particular hardware and/or software elements of the radar
Implementation Method 2
calculating a probability of the presence of false targets based on equations for the propagation of the electromagnetic waves in the environment of the radar
Data Source
AI summary
A method for radar detection of targets includes: determining digital data representative of the radar environment in real time, calculating a probability of existence of mock targets in a plurality of regions of the radar environment on the basis of the digital data representative of the radar environment, receiving digital data corresponding to at least one radar target, transmitted by the radar, including digital location data of the at least one radar target, calculating a reliable confidence index associated with the at least one radar target according to the probability of existence of mock targets in the region where the at least one radar target is located.