Radar Background Map for Stationary Object Motion Detection
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Solution Overview
Problem
Existing methods for detecting motion using radar detectors often trigger erroneously on stationary objects that exhibit motion, such as flags or trees, leading to unwanted events.
Innovation Solution
A method that evaluates radar echoes over time to determine if an object is stationary by calculating its maximum deviation distance or directional shift angles, and uses a map of background objects to differentiate between true moving objects and stationary objects exhibiting motion, thereby adjusting sensitivity and reducing false triggers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar detectors are used to detect motion of objects in a scene, then velocity of moving objects can be detected, but stationary objects exhibiting motion (flags, trees, bushes) cause erroneous triggering events
Solution Approach 1:
The system performs preliminary actions by creating and maintaining a map of background objects before motion detection occurs. This map is continuously updated with object locations and characteristics, allowing the system to pre-identify stationary objects that exhibit motion. When motion detection is performed, the system can immediately compare detected objects against this pre-established map to filter out false positives from stationary objects like flags and trees.
Solution Approach 2:
The system implements feedback by continuously monitoring radar echoes over time and using this information to update the background object map. The detected objects are fed back into the system to refine the map, which in turn improves subsequent motion detection accuracy. This closed-loop feedback mechanism allows the system to adapt to changing environmental conditions and improve its ability to distinguish stationary objects from truly moving objects.
2Measurement precision
If sensitivity of motion detection is increased to detect all moving objects, then more moving objects can be detected, but false alarms from stationary objects increase
Solution Approach 1:
The system segments the detection process into distinct phases: background mapping, motion detection, and verification. By dividing the detection process and maintaining separate data structures for background objects and detected objects, the system can apply different processing rules to each segment. This segmentation allows high sensitivity in motion detection while maintaining reliability through the verification phase that compares detections against the background map.
Solution Approach 2:
The background object map serves as an intermediary between the raw radar detections and the final motion detection output. This intermediary structure stores information about stationary objects and mediates the comparison between detected objects and known background objects. The map acts as a buffer that allows the system to maintain high detection sensitivity while filtering out false alarms through the intermediary comparison process.
3Measurement precision
If radar echoes are monitored continuously over time, then accuracy of distinguishing stationary and moving objects improves, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-processing radar echoes to extract and store essential characteristics of background objects in a structured map format. By preparing this background information in advance and organizing it efficiently, the system reduces the computational burden during real-time motion detection. The pre-organized map allows for faster comparisons and reduces the complexity of processing continuous radar data streams.
Solution Approach 2:
The system changes parameters by focusing on specific key parameters (location, velocity characteristics) rather than processing all raw radar data in full detail. By transforming the radar echo data into a simplified representation that captures only the essential parameters needed for distinguishing stationary and moving objects, the system maintains high accuracy while reducing computational complexity. This parameter transformation allows efficient processing of continuous monitoring data.
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 improves the accuracy of detecting moving objects by effectively distinguishing between stationary and moving objects, reducing false alarms and enhancing the reliability of motion detection systems.
Implementation Method 1
detecting over time radar echoes, each comprising radar echo information pertaining to a location of a moving object within the scene and a velocity of the moving object
Implementation Method 2
A radar detector configured to detect radar echoes with a predetermined detection repetition frequency
Data Source
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AI summary
The disclosure relates to a method (200) for, in a map (210) of background objects, registering presence of a stationary object exhibiting motion (205) at a location in a scene (202) monitored by a radar detector (204), the method comprising: detecting (S102) over time radar echoes (206) at a radar detector (204) monitoring a scene (202), wherein the moving object (201) is one of a true moving object (207) or a stationary object exhibiting motion (205); evaluating (S104) the over time detected radar echoes (206) for finding a stationary object exhibiting motion (205); registering (S106) presence of the stationary object exhibiting motion (205) at a location (220B), corresponding to the location (220A) of the stationary object exhibiting motion (205), in a map of background objects (210). The disclosure further relates to a method for detecting moving objects using a radar detector (204) wherein the map of background objects (210) is used as input.