Radar Object Verification Using Feature Extraction
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Solution Overview
Problem
Traditional object recognition techniques are time and resource intensive, and often produce false positives or false negatives, particularly in identifying or verifying objects from radar images.
Innovation Solution
A method and apparatus for performing object verification using radar images by extracting features such as amplitude, phase, and magnitude from radar images, and determining similarity between them using a mapping function, which can be learned using techniques like support vector machines or deep neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional object recognition techniques are used, then object identification can be performed, but computational time and resources are excessive
Solution Approach 1:
The patent extracts and utilizes specific features from radar images (amplitude, phase, magnitude) to perform object verification. By focusing on extracting only the necessary features rather than processing entire images through traditional recognition algorithms, the system achieves faster verification with reduced computational time and resources.
2Reliability
If traditional object recognition techniques are used, then objects can be identified, but false positive and false negative rates increase
Solution Approach 1:
The patent transforms radar image data into different parameter domains (amplitude, phase, magnitude) and uses these transformed parameters for verification. By changing the parameter representation and using a mapping function to compare features across different images, the system improves classification accuracy and reduces false positives and false negatives compared to traditional recognition methods.
Data Source
AI summary
Techniques and systems are provided for performing object verification using radar images. For example, a first radar image and a second radar image are obtained, and features are extracted from the first radar image and the second radar image. A similarity is determined between an object represented by the first radar image and an object represented by the second radar image based on the features extracted from the first radar image and the features extracted from the second radar image. A determined similarity between these two sets of features is used to determine whether the object represented by the first radar image matches the object represented by the second radar image. Distances between the features in the two radar images can optionally also be compared and used to determine object similarity. The objects in the radar images may optionally be faces.