FMCW Radar Phase Imbalance Detection from Range-Velocity Maps
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Solution Overview
Problem
Existing radar sensors face issues with phase imbalance due to ball breaks, which affect signal transmission and reception, leading to reduced performance and accuracy, particularly in automotive applications like adaptive cruise control and blind spot detection, and current hardware-based detection methods cause noise figure degradation or require significant MMIC area.
Innovation Solution
A signal processing approach for phase imbalance detection in frequency-modulated continuous-wave (FMCW) radar sensors that generates an integrated range-velocity map, identifies peaks, and determines phase imbalances using data from multiple radar channels, allowing for real-time detection and calibration without additional MMIC circuitry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hardware-based detection methods are used for phase imbalance detection, then detection capability is provided, but noise figure degradation occurs or significant MMIC area is required
Solution Approach 1:
The patent replaces hardware-based detection circuits with a signal processing approach that uses existing radar data. Instead of adding dedicated detection hardware that would degrade noise figure, the system processes existing range-velocity map data through computational algorithms to detect phase imbalances, thereby eliminating the need for additional MMIC circuitry while maintaining detection capability
Solution Approach 2:
The system uses its own existing operational data (range-velocity maps from normal radar operation) to detect phase imbalances. By extracting data from the same channels already being used for target detection and processing this data through algorithms, the system performs self-diagnosis without requiring separate detection hardware or affecting the noise figure
2Reliability
If hardware-based detection methods are used for phase imbalance detection, then detection capability is provided, but significant MMIC area is required
Solution Approach 1:
The patent replaces hardware-based detection circuits with a signal processing approach that uses existing radar data. Instead of adding dedicated detection hardware that would degrade noise figure, the system processes existing range-velocity map data through computational algorithms to detect phase imbalances, thereby eliminating the need for additional MMIC circuitry while maintaining detection capability
Solution Approach 2:
The system performs multiple functions using the same processing resources. The range-velocity map processing that is already performed for target detection is also utilized for phase imbalance detection. By extracting data from the same channels already being used for target detection, the system achieves multi-functionality without requiring separate detection hardware or affecting the noise figure
Data Source
AI summary
A radar device may generate an integrated range-velocity map by combining data from a plurality of range-velocity maps. Each range-velocity map may be associated with a respective radar channel from a plurality of radar channels. The radar device may identify a first peak in the integrated range-velocity map. The first peak may indicate one or more radar targets in the integrated range-velocity map and being identified by a first bin having a first range-velocity bin index. The radar device may determine a first data set by extracting, from each range-velocity map, data that is included in a respective bin associated with the first range-velocity bin index. The radar device may process the first data set to determine a first set of phase imbalances associated with the plurality of radar channels.