Radar Rain Clutter Suppression via Local Data Change Analysis
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Solution Overview
Problem
Conventional radar systems face difficulties in effectively suppressing rain clutter, leading to inaccurate target object detection due to high amplitude values from reflection signals, which are not adequately addressed by existing methods.
Innovation Solution
A method and device that temporarily store detection data within a predetermined geographical range, identify the type of reflection echoes based on changes in data values between physically-close locations, and generate mask image data to suppress rain clutter by adjusting the detection data values according to predetermined thresholds and processing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional rain clutter suppression methods are used, then some clutter suppression is achieved, but the suppression is ineffective against highly-random clutter and requires huge amounts of stored data
Solution Approach 1:
The patent divides the detection data into multiple geographical ranges (first, second, third, and fourth ranges) and processes each segment separately. By calculating change counts within specific segments rather than processing all data globally, the method reduces computational complexity and data storage requirements while maintaining effective clutter suppression.
Solution Approach 2:
The patent performs preliminary processing by temporarily storing detection data and calculating change counts between adjacent locations before final target object determination. This preliminary analysis of data variations allows the system to identify rain clutter patterns early, reducing the need for extensive additional data storage and processing later.
2Reliability
If conventional clutter suppression methods are used, then some processing is performed, but the methods cannot effectively suppress rain clutter under various rain conditions
Solution Approach 1:
The patent employs dynamic thresholds for change count comparison that can adapt to different detection scenarios. By comparing the calculated change count against a predetermined threshold, the system dynamically adjusts its sensitivity to detect rain clutter under varying conditions, making it adaptable to different rain intensities and patterns rather than using fixed processing rules.
Solution Approach 2:
The patent changes the parameter being analyzed from absolute amplitude values to the rate of change (difference) between adjacent detection data values. This parameter transformation allows the system to effectively distinguish rain clutter from target objects across various rain conditions, as the change pattern differs fundamentally between clutter and legitimate targets regardless of rain intensity.
3Measurement precision
If detection data is processed without change analysis, then processing is simpler, but target object detection accuracy decreases due to rain clutter interference
Solution Approach 1:
The patent applies local quality analysis by examining the change count at each specific detection data location independently. Instead of applying global processing rules, the system calculates the difference between each detection data value and its adjacent values, then compares this local change count against thresholds to determine if rain clutter is present at that specific location, thereby improving detection accuracy without requiring complex global processing.
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 accurately and effectively suppresses rain clutter, allowing for clear display of target objects by differentiating between target objects and rain clutter through data analysis and image processing, thereby improving radar system performance.
Implementation Method 1
a radar apparatus which transmits electromagnetic waves at a predetermined frequency as detection signals
Implementation Method 2
receive reflection waves of the detection signals
Data Source
AI summary
This disclosure provides a method of detecting a target object by receiving reflection echoes of detection signals transmitted sequentially from a revolving antenna, and by detecting a target object based on detection data resulted from sampling reception signals at a predetermined time interval. The method comprises temporarily storing the detection data within a predetermined geographical range, and identifying the type of the reflection echo based on a change between values of the detection data at physically-close locations within the predetermined geographical range.