Radar Signal Processing Device for Vehicle Object Identification
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Solution Overview
Problem
Existing vehicle-mounted radar systems face challenges in accurately identifying objects for braking decisions due to low signal-to-noise ratios at long or close distances, leading to incorrect identification of objects.
Innovation Solution
A radar signal processing device that extracts first and second feature quantities from radar measurements, calculates an attribution degree using a database, and accumulates scores over time to determine object categories, reducing the likelihood of incorrect identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If object identification is performed based on received power and signal characteristics, then identification speed is improved, but identification accuracy deteriorates when signal-to-noise ratio is low
Solution Approach 1:
The system performs preliminary actions by accumulating measurement data over multiple cycles before making identification decisions. The accumulation/instantaneous score calculation block collects signal characteristics across multiple measurement cycles and accumulates scores, enabling reliable identification even when individual measurements have low signal-to-noise ratios. This preliminary data accumulation resolves the contradiction by preparing sufficient information in advance to ensure both speed and accuracy.
Solution Approach 2:
The system implements feedback mechanisms where identification results from previous cycles inform subsequent measurements and scoring. The attribution degree calculation block continuously refines object categorization based on accumulated evidence, and the system adjusts its determination based on feedback from multiple measurement cycles. This feedback loop ensures that identification accuracy improves over time while maintaining efficient processing speed.
2Loss of time
If determination is made based on single measurement results, then processing time is reduced, but reliability of braking decisions deteriorates
Solution Approach 1:
The system performs preliminary data accumulation across multiple measurement cycles before making final braking decisions. The data storage processing block stores first feature quantities and associates them with objects in time series, preparing a comprehensive data foundation in advance. This preliminary action ensures that when braking decisions are required, they are based on accumulated reliable evidence rather than single potentially erroneous measurements, thus maintaining both speed and reliability.
Solution Approach 2:
The system performs more measurements than strictly necessary for immediate decisions, accumulating data across multiple cycles beyond the minimum required for single-shot determination. The accumulation/instantaneous score calculation block processes more measurement data than a single-cycle system would use, providing an excessive amount of information that enhances decision reliability while the system manages processing time efficiently through selective accumulation.
3Measurement precision
If dictionary checking is performed for object identification, then identification accuracy is improved, but data accumulation requirements increase system complexity
Solution Approach 1:
The system segments the identification process into distinct functional blocks: first feature quantity extraction, data storage and association, second feature quantity extraction, attribution degree calculation, and accumulation/instantaneous score calculation. Each block performs a specific function with well-defined inputs and outputs, reducing overall system complexity while maintaining high identification accuracy through the segmented processing pipeline.
Solution Approach 2:
The data storage processing block serves multiple functions: it stores first feature quantities, associates them with objects in time series, and provides data for subsequent feature extraction and scoring. This multi-functional component reduces the need for separate dedicated structures for each function, thereby reducing system complexity while maintaining comprehensive data management for accurate identification.
Data Source
AI summary
A radar signal processing device capable of performing a highly accurate object identification is obtained. A first feature quantity related to a relative distance and a relative speed to an object, the direction and the reflection intensity of the object, which are extracted by a first feature quantity extraction block, is made identical in time series in a data storage processing block; a second feature quantity is extracted by a second feature quantity extraction block; one in which an instant score is accumulated in a cycle direction to the distribution of the second feature quantity related to a predetermined category calculated by an attribution degree calculation block is calculated as an accumulation score by an accumulation/instant score calculation block; and a category of the object is determined by an object determination block on the basis of the accumulation score calculated by the accumulation/instant score calculation block.