Cascaded MMIC Radar Signal Processing for Angular Resolution
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Solution Overview
Problem
There is an increasing demand for improved angular resolution and processing capabilities in radar systems, particularly for autonomous driving applications, which requires efficient signal processing across multiple receiving channels, but existing MMIC units are limited by their size and pin count, necessitating a distributed processing approach.
Innovation Solution
The implementation of a distributed processing method using cascaded MMIC units with identical or similar structures, where each unit performs partial computations and communicates through a cascaded link, with a digital processing master and RF master device coordinating the computation and communication, enabling efficient angular and elevation processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed processing using cascaded MMIC units is implemented, then processing capability and angular resolution are improved, but device complexity increases
Solution Approach 1:
The radar signal processing system is divided into multiple MMIC units, each handling a specific portion of the receiving channels. Each unit performs partial FFT computations and passes intermediate results through cascaded links to subsequent units, enabling distributed processing of radar signals while maintaining modular architecture
Solution Approach 2:
The system transitions from single-unit processing to multi-unit cascaded processing, adding a dimensional aspect to the processing architecture. Intermediate results are conveyed through cascade links between units, creating a multi-stage processing pipeline that enhances computational capacity beyond what a single unit can provide
2Measurement precision
If more receiving channels are processed, then angular resolution is improved, but memory usage and hardware resources increase
Solution Approach 1:
The memory requirements are segmented across multiple MMIC units rather than concentrated in a single unit. Each unit stores only the intermediate results for its assigned receiving channels, and the cascade links enable distributed memory access patterns that reduce the memory burden on any single unit while supporting processing of multiple receiving channels
Solution Approach 2:
Each MMIC unit performs partial FFT computations on a subset of receiving channels rather than processing all channels completely. This partial action approach allows the system to handle more channels collectively across multiple units while each unit uses minimal memory resources for its specific computation task
Data Source
AI summary
A radar device including at least three subcircuits, wherein each subcircuit has a cascade input port and a cascade output port and is chained such that the cascade output port of a first subcircuit is connected to the cascade input port of a subsequent subcircuit, the cascade input port of the last subcircuit of the chain is connected to the cascade output port of its preceding subcircuit, and the cascade output port of the last subcircuit of the chain is connectable to an external device, and wherein the at least three subcircuits are configured to conduct a radar computation in a distributed manner such that intermediate results are conveyed towards the last subcircuit of the chain which is configured to combine these results and supply them towards its cascade output port.