Radar Device Sensor Fusion Database Update
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Solution Overview
Problem
Existing radar devices and sensor fusion systems face challenges in achieving high identification accuracy due to reliance on signal strength features, high calculation loads, large memory requirements, and potential for erroneous determinations, especially in varying conditions such as beam patterns and object materials, which can lead to delayed responses in critical situations.
Innovation Solution
A radar device with an identification system that updates a database using attribution degrees calculated from multiple sensor inputs, including relative distance, speed, angle, and reflection strength, allowing for accurate object categorization and improved performance even with limited data points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a determination is performed on the basis of only a feature quantity derived from signal strength, then the device complexity is reduced, but the measurement precision deteriorates when the measurement result cannot be normally obtained
Solution Approach 1:
The patent combines multiple feature quantities (signal strength, distance, angle, identification results from other sensors) into a unified determination process. The determination unit integrates these diverse inputs to classify objects, thereby maintaining low device complexity while improving measurement precision through multi-parameter fusion rather than relying on signal strength alone.
Solution Approach 2:
The radar device is enhanced with multi-functional capability by incorporating not only signal strength measurement but also distance measurement, angle measurement, and integration with other sensor identification results. This universal approach allows the single determination unit to handle various object classification scenarios accurately without requiring separate specialized systems.
2Measurement precision
If a dictionary is created by obtaining a large number of data for performing a highly accurate estimation, then the measurement precision is improved, but the device complexity and memory requirements increase
Solution Approach 1:
Instead of requiring a complete dictionary with exhaustive data for all possible objects, the patent uses a determination unit that processes only the necessary feature quantities (signal strength, distance, angle, and other sensor inputs) on-demand. This partial action approach achieves sufficient estimation accuracy without the burden of maintaining and searching large comprehensive databases.
Solution Approach 2:
The patent extracts only the essential feature quantities needed for accurate object classification (signal strength, distance, angle, and identification results from other sensors) rather than processing all available data. This extraction principle enables high measurement precision while minimizing device complexity by focusing on the most relevant parameters.
3Measurement precision
If data accumulation is required for calculating variations, then the measurement precision is improved, but the response time increases which may delay handling for temporally tight situations
Solution Approach 1:
The radar device performs preliminary measurements of distance, angle, and signal strength continuously and maintains readiness to process identification requests. By having these base measurements prepared in advance and integrating them with pre-available identification results from other sensors, the system can make accurate determinations without requiring time-consuming data accumulation for variation calculations.
Solution Approach 2:
The determination unit utilizes feedback from other sensor devices (such as camera identification results) to supplement radar measurements. This feedback mechanism allows the system to achieve high determination accuracy using existing parallel sensor data rather than accumulating additional radar data over time, thereby maintaining fast response times for urgent situations.
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
The radar device achieves high identification accuracy and efficient object classification by dynamically updating its database based on attribution degrees from multiple sensors, reducing errors and improving response times in dynamic environments.
Implementation Method 1
vehicle-mounted radar device
Implementation Method 2
radar reflection sectional area
Data Source
AI summary
In order to improve accuracy of kind identification of a detected object in a radar device provided in a sensor fusion system, information of the result of kind identification by a camera device provided in the sensor fusion system is given to the radar device and an attribution degree database that is used for identification determination by the radar device during the operation of the sensor fusion system is updated by a database update block.