Adaptive Radar Processing with Speed-Steering ROI Selection
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Solution Overview
Problem
Processing radar data for autonomous vehicles is computationally expensive due to the need to process large volumes of data from a wide field of view, which increases hardware requirements and costs.
Innovation Solution
Adaptive region of interest (ROI) is created based on vehicle speed and steering wheel angle to selectively process radar data, limiting the range and angular dimensions, thereby reducing computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar data from the full field of view is processed, then detection coverage is improved, but computational cost increases
Solution Approach 1:
The patent segments the radar data processing task by dividing the full field of view into multiple regions of interest (ROIs) based on vehicle speed and steering angle. Only data within these segmented ROIs is processed in detail, while other regions receive reduced or no processing, thereby reducing computational cost while maintaining detection coverage for critical areas.
Solution Approach 2:
The patent applies local quality by varying the processing intensity and ROI selection based on local driving conditions. At different speeds and steering angles, different regions are prioritized for processing - for example, at high speeds the forward view is prioritized, while at low speeds side views may be emphasized. This ensures computational resources are allocated to the most relevant regions rather than uniformly processing all data.
2Measurement precision
If a wide field of view is processed, then detection accuracy is improved, but hardware requirements increase
Solution Approach 1:
The patent implements dynamic ROI adjustment based on vehicle speed and steering wheel angle. The system dynamically changes which regions are processed and at what resolution, adapting to current driving conditions. This dynamic approach maintains high detection accuracy for relevant regions while reducing processing load, thereby lowering hardware requirements compared to static full-field processing.
Solution Approach 2:
The patent changes processing parameters (ROI boundaries, processing intensity) based on vehicle speed and steering angle parameters. By adjusting these parameters dynamically, the system maintains detection accuracy for critical regions while reducing overall computational burden, thus lowering hardware requirements without sacrificing essential detection capabilities.
3Productivity
If adaptive ROI selection based on speed and steering angle is implemented, then resource usage is optimized, but processing complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-defining multiple ROI configurations corresponding to different speed and steering angle ranges. Rather than calculating optimal ROIs in real-time, the system selects from pre-computed configurations based on current sensor inputs, thereby optimizing resource usage while minimizing the added processing complexity of adaptive selection.
Data Source
AI summary
A computer implemented method for radar data processing includes the following steps carried out by computer hardware components: acquiring radar data from a radar sensor mounted on a vehicle; determining at least one of a speed of the vehicle or a steering wheel angle of the vehicle; and determining a subset of the radar data for processing based on the at least one of the speed of the vehicle or the steering wheel angle of the vehicle.