Radar Signal Compression After 1D FFT for Memory-Limited ICs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Embedded FMCW radar systems face memory constraints due to the significant amount of data required for processing radar signals, limiting the capabilities of radar transceiver ICs and increasing costs.
Innovation Solution
The implementation of compression techniques, such as block floating point (BFP), bit packing (PAC), exponential Golomb (EG), and variable bit width BFP (VBBFP), to compress radar signals after the 1D FFT, allowing for reduced memory requirements while maintaining signal processing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If larger memory capacity is included in radar transceiver ICs, then more radar data can be stored, but die size and cost increase
Solution Approach 1:
The patent applies compression algorithms to change the parameter of data representation, transforming raw radar data into compressed form with reduced bit width. This allows more data to be stored in the same physical memory capacity, effectively increasing the quantity of storable data without adding physical memory components, thereby avoiding increase in die size and cost.
2Quantity of substance
If larger memory capacity is included in radar transceiver ICs, then more radar data can be stored, but cost increases
Solution Approach 1:
By implementing software-based compression algorithms, the patent changes the data storage parameter from raw format to compressed format. This approach allows the system to store more radar data using the same physical memory, eliminating the need to purchase and integrate larger memory components, thereby reducing manufacturing cost while maintaining or enhancing storage capacity.
3Quantity of substance
If compression is applied to radar data, then memory requirements are reduced, but processing complexity increases
Solution Approach 1:
The patent applies compression immediately after the 1D FFT stage, before data is stored in memory. This preliminary compression action reduces the data volume that needs to be stored, thereby reducing memory requirements. The compression is performed once on the range values before storage, and the compressed data is subsequently used in 2D FFT processing, balancing the added processing complexity with significant memory savings.
Data Source
AI summary
A radar system is provided that includes a compression component configured to compress blocks of range values to generate compressed blocks of range values, and a radar data memory configured to store compressed blocks of range values generated by the compression component. In an example, the compression component parameter determination engine to determine a compression parameter for a type of compression to yield a compressed output of the block of range values that is less than or equal to a specified size. The compression parameter may be a scale factor, or may be a Golomb parameter and a scale factor, depending on the type of compression. The compression component further includes an encoder to compress, using the type of compression, the block of range values to generate a compressed block of range values based on the compression parameter.