Terrain-Following Radar Polarimetry for Weather Clutter Rejection
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Solution Overview
Problem
Terrain-following radars face challenges in distinguishing between weather and terrain, leading to incorrect commands for pilots to climb over weather, which can be hazardous.
Innovation Solution
The system employs dual-polarization radar data to calculate Correlation Coefficient (CC), Differential Reflectivity (ZDR), and Specific Differential Phase (KDP) and applies discriminator logic to differentiate between rain and non-rain returns, allowing for the rejection of weather returns while maintaining terrain detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If weather detection is enhanced to detect clouds and rain, then weather observation capability is improved, but false terrain detection occurs leading to incorrect climb commands
Solution Approach 1:
The patent applies parameter changes by utilizing dual-polarization radar data to compute specific differential phase (KDP), correlation coefficient (CC), and differential reflectivity (ZDR). These parameter transformations enable the discrimination of rain from terrain by analyzing the electromagnetic wave interaction characteristics with different targets, thereby resolving the contradiction between enhanced weather detection and maintained terrain detection reliability
Solution Approach 2:
The patent introduces an intermediary classification system that uses discriminator logic based on KDP, CC, and ZDR parameters to act as a mediator between raw radar returns and terrain following commands. This intermediary layer classifies radar returns as either weather or terrain before generating climb commands, preventing false terrain detection while preserving accurate weather observation
2Reliability
If dual-polarization processing is applied to discriminate rain from terrain, then terrain detection reliability is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-computing the three polarization parameters (KDP, CC, ZDR) from dual-polarization radar data before classification. By preparing these parameters in advance through systematic processing steps, the system reduces the complexity of the final discrimination logic while maintaining high terrain detection reliability
Solution Approach 2:
The patent segments the complex discrimination problem into three distinct parameter analyses (KDP for rain intensity, CC for target uniformity, ZDR for particle shape). This segmentation allows each parameter to be processed and evaluated independently through specific discriminator logic, reducing overall computational complexity compared to analyzing raw radar data as a single complex signal
Data Source
AI summary
Embodiments for a terrain following (TF) radar configured for use in an airborne system are generally described herein. In some embodiments, a radar return comprising dual polarimetry radar data is processed to determine a Correlation Coefficient (CC), a Differential Reflectivity (ZDR), and a Specific Differential Phase (KDP). Discriminator logic is applied to the CC, the ZDR and the KDP to determine whether the radar return comprises solely rain. Further signal processing may be performed on the radar return when the radar return does not comprise solely rain. When the radar signal comprises solely rain, the radar return is tagged as a rain return. Applying the discriminator logic may include applying linear and/or quadratic functions to the CC, the ZDR and the KDP to determine whether the radar return comprises solely rain.