Radar Signal Processing With Hierarchical Doppler Filtering
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Solution Overview
Problem
Existing radar signal processing methods in automotive applications discard a significant amount of information, leading to sparse perception of the environment, despite advancements in radar hardware capabilities for capturing large data sets.
Innovation Solution
A method involving a hierarchical filter bank and discrete wavelet transform is applied to radar signals, allowing for efficient extraction of Doppler features with higher time resolution and retention of information, using a Haar wavelet transform to simplify processing and minimize computing power and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If classical radar processing methods are used to reduce large maps to point targets, then computing power and memory requirements are minimized, but information loss occurs and environmental perception becomes sparse
Solution Approach 1:
The patent segments the processing of large radar maps into hierarchical levels. Instead of processing the entire large map at once, it divides the processing into multiple scales or resolutions, allowing information to be retained at different levels of detail while managing computational complexity through progressive refinement from coarse to fine scales.
2Loss of information
If large sized 3D arrays are processed in a naive way to produce image-like information, then environmental perception is enhanced, but computing power and memory requirements increase significantly
Solution Approach 1:
The patent implements dynamic processing where the level of detail and processing intensity adapts to the specific scene requirements. Rather than uniformly processing all data at maximum resolution, the system dynamically adjusts processing depth based on detected objects, their importance, and scene complexity, optimizing the balance between perception quality and computational energy consumption.
3Measurement precision
If classical processing methods are used to extract detection candidates, then computing resources are conserved, but Doppler features are measured with lower time resolution
Solution Approach 1:
The patent applies preliminary filtering and preprocessing steps that prepare the data in advance for more precise Doppler measurements. By performing initial range processing, clutter suppression, and data organization before the main Doppler analysis, the system enables higher precision measurements without requiring excessive computational resources during the critical measurement phase.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more efficient radar processing that retains a larger amount of information, providing enhanced environmental perception with improved spatial and temporal resolution, allowing for accurate detection and tracking of multiple moving objects.
Implementation Method 1
adjusting each of the plurality of radio waves based on an angle of incidence of the reflected radio wave, and the motion of the antenna array; and filtering each of the plurality of adjusted processed radio waves through a hierarchical filter bank comprising a plurality of filters to receive a plurality of output images representing the motion of the object
Data Source
AI summary
A method for processing radar signals includes receiving multiple radio waves reflected from at least one object and received by an antenna array. The method includes processing each of the reflected radio waves to determine a range from the antenna array to the at least one object. The method includes adjusting each of the processed radio waves based on a respective angle of incidence of the reflected radio wave and the motion of the antenna array. The method includes filtering the adjusted processed radio waves through a hierarchical filter bank including multiple filters to receive multiple output images representing the motion of the object.