Radar Object Detection in Inclement Weather
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Solution Overview
Problem
Radar systems in mobile platforms, such as autonomous vehicles, face challenges in accurately detecting objects in inclement weather due to signal degradation from rain or snow, which increases noise power and reduces the ability to distinguish reflection signals from objects.
Innovation Solution
The system determines weather conditions by measuring noise floors and adjusting radar sensor settings, including beam width and integration time, to enhance object detection accuracy. It uses multiple radar sensors arranged to minimize spillover effects and operates in sequential time slots to form detection regions, emitting and receiving signals with preset codes to exclude self-emitted signals and focus on object reflections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar sensors operate in inclement weather conditions, then object detection capability is maintained, but noise power increases and detection accuracy deteriorates
Solution Approach 1:
The system dynamically changes radar operating parameters including beam width and integration time based on detected weather conditions. In inclement weather, the beam width is adjusted to reduce noise power and integration time is modified to optimize signal detection, thereby maintaining detection capability while compensating for increased noise and reduced accuracy
Solution Approach 2:
The system implements a feedback mechanism where noise floor measurements are continuously monitored and used to determine weather conditions. This feedback loop enables the radar to adapt its operating parameters in real-time based on environmental conditions, allowing it to maintain reliable object detection despite deteriorating accuracy in inclement weather
2Measurement precision
If beam width is decreased to enhance signal directivity, then object detection accuracy in inclement weather improves, but detection region coverage is reduced
Solution Approach 1:
The system dynamically adjusts beam width based on weather conditions and target characteristics. Rather than using a fixed beam width, the radar can narrow the beam in inclement weather to improve signal directivity and detection accuracy while potentially sweeping or steering the beam to maintain adequate coverage of the detection region
3Measurement precision
If integration time is increased to improve signal detection, then object detection accuracy improves, but response speed decreases
Solution Approach 1:
The system dynamically adjusts integration time based on weather conditions and signal characteristics. In inclement weather with higher noise power, longer integration times are used to improve signal detection accuracy. When conditions improve or rapid response is needed, integration time is reduced to maintain faster response speed, optimizing the trade-off between accuracy and speed
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 object detection in adverse weather by dynamically adjusting radar settings based on weather conditions, reducing noise interference and enhancing signal directivity, thereby improving the ability to detect objects in inclement conditions.
Implementation Method 1
Radar is used to detect an object and classify the object. Radar is also used to detect and analyze a movement of the object.
Implementation Method 2
ascertaining a first average power of a first backscattered radar signal, ascertaining a second average power of a second backscattered radar signal
Implementation Method 3
determining a weather condition based on a noise floor measured by at least one radar sensor from among a plurality of radar sensors arranged separately from one another
Data Source
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AI summary
An object detection method and apparatus is disclosed, where the object detection method includes determining a weather condition based on a noise floor measured in an elevated direction, and detecting an object based on comparing a signal level of a target signal measured in a depressed direction and a threshold level corresponding to the determined weather condition.