Radar Reflection Graph Classification Without ROI Processing
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Solution Overview
Problem
Conventional methods for determining the classification of objects based on radar spectra require significant computational effort due to the use of Region of Interest (ROI), which hinders efficient processing.
Innovation Solution
A method that determines classification by constructing two graphs from radar reflections and embeddings, without initially defining ROIs, and uses graph convolutions to extract features, integrating spatial coordinates and Doppler velocities, thereby reducing computational effort and improving classification accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Region of Interest (ROI) is used for object classification, then classification accuracy is improved, but computational effort increases significantly
Solution Approach 1:
The radar spectrum is divided into multiple sections, with embeddings determined for each section containing radar reflections. This segmentation allows processing of specific spectral regions independently, improving both accuracy through focused analysis and efficiency by avoiding unnecessary processing of entire spectra.
Solution Approach 2:
The patent extracts only the relevant sections from the radar spectrum that contain radar reflections, rather than processing the entire spectrum. By taking out and processing only the meaningful portions (sections with reflections), computational effort is reduced while maintaining classification accuracy.
2Measurement precision
If detailed spectral analysis is performed for each section, then classification precision is improved, but processing time increases
Solution Approach 1:
Embeddings are determined in advance for each spectral section containing radar reflections. These pre-computed embeddings are then used as input for graph construction and classification, eliminating the need for repeated detailed analysis during the classification process itself.
Solution Approach 2:
The patent performs detailed analysis only on partial portions of the spectrum - specifically, only on sections that contain radar reflections. By applying detailed spectral analysis selectively rather than uniformly across the entire spectrum, processing time is reduced while maintaining precision where it matters most.
Data Source
AI summary
A device and method for determining a classification of an object. A radar spectrum which includes radar reflections is determined as a function of sensor data from a radar sensor. Embeddings of sections from the radar spectrum which include at least one radar reflection are determined and each is assigned to a node of a first graph. Edges are determined as a function of pairwise distances between the embeddings which are assigned to the nodes. For each edge, a feature for the edge is determined as a function of the embeddings of two nodes which are connected to one another by the edge. For each node, a feature for the node is determined as a function of the features for the edges which connect the node to another node. A characteristic quantity is provided for each radar reflection as a function of the sensor data.