Variable Compression FFT Radar Signal Processing
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Solution Overview
Problem
FMCW radar systems face high storage requirements and resource intensity due to the need to store and process large amounts of data, which can lead to degradation in signal-to-noise ratio (SNR), particularly in reducing storage needs while maintaining effective object detection capabilities.
Innovation Solution
The implementation of a method that involves determining FFT values for signal samples, variably compressing these values at different non-zero compression levels, and storing the compressed data, allowing for later decompression and further processing to maintain or improve SNR, thereby reducing storage needs and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compressed to reduce storage requirements, then storage needs are reduced, but signal-to-noise ratio degrades
Solution Approach 1:
The patent applies different compression levels to different portions of the radar signal data based on their importance. Critical signal components are compressed at lower levels to preserve SNR, while less critical data is compressed more aggressively, achieving overall storage reduction without uniformly degrading signal quality
Solution Approach 2:
The system dynamically adjusts compression parameters based on signal characteristics, signal-to-noise ratio thresholds, and storage requirements. By changing compression parameters adaptively rather than using fixed compression, the system optimizes the balance between storage efficiency and signal quality preservation
2Reliability
If all signal samples are stored at full resolution, then signal-to-noise ratio is maintained, but storage requirements and resource intensity increase
Solution Approach 1:
The radar signal data is segmented into different components (e.g., signal portions and noise portions, or different time/frequency segments). Each segment is compressed at an appropriate level based on its characteristics, allowing the system to maintain SNR for critical segments while reducing storage for less critical segments
Solution Approach 2:
Instead of applying uniform compression to all data, the system applies compression selectively - using full or near-full resolution storage for the most critical signal portions where SNR must be maintained, and applying compression to other portions where storage efficiency is prioritized
Data Source
AI summary
Signal processing comprising, first, determining a plurality of fast Fourier transform (FFT) values corresponding to each sample in a plurality of signal samples, second, variably compressing ones of the FFT values at different non-zero levels of compression, and third, storing the variably compressed ones of the FFT values.