Radar Signal Pairing Discrimination
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Solution Overview
Problem
Current radar systems face challenges in accurately pairing peak signals from up and down periods to derive correct target information, leading to potential mis-pairing and incorrect vehicle control due to noise interference and increased processing load when calculating Mahalanobis distances.
Innovation Solution
A radar apparatus that extracts peak signals and pairs them using a discrimination function based on multiple parameter values, including peak power, angular differences, and angular spectrum differences, to select correctly paired data and reduce processing load by incorporating information on past consecutive targets and object images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Mahalanobis distance calculation is used to select normal-paired data, then pairing accuracy is improved, but processing load increases
Solution Approach 1:
The patent segments the parameter space by classifying paired data into low-reliability and high-reliability regions based on parameter thresholds. This segmentation allows the system to apply different processing strategies: Mahalanobis distance calculation only for low-reliability regions (where pairing accuracy is critical) and threshold-based filtering for high-reliability regions (where processing speed is prioritized), thereby resolving the contradiction between pairing accuracy and processing load.
Solution Approach 2:
The patent applies local quality by using different evaluation criteria for different regions of the parameter space. For paired data in the low-reliability region (where parameters indicate potential mis-pairing), the system applies the computationally intensive Mahalanobis distance calculation. For paired data in the high-reliability region, simpler threshold-based methods are used. This localized application of quality assessment methods optimizes both accuracy and processing efficiency.
2Measurement precision
If multiple parameters are used for pairing discrimination, then pairing accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary action by first evaluating paired data against predefined parameter thresholds before applying Mahalanobis distance calculation. This preliminary filtering identifies and eliminates clearly reliable paired data, so that the computationally intensive Mahalanobis calculation is only applied to cases where it is truly necessary. This staged approach significantly reduces processing time while maintaining high pairing accuracy.
Solution Approach 2:
The patent applies partial action by selectively applying the full multi-parameter discrimination (including Mahalanobis distance) only to paired data that falls into the low-reliability region, rather than applying it uniformly to all paired data. This partial application of the rigorous discrimination method reduces overall processing time while still achieving high pairing accuracy for the critical cases.
3Productivity
If peak signals are paired based on simple conditions, then processing speed is maintained, but mis-pairing occurs due to noise
Solution Approach 1:
The patent introduces an intermediary mechanism: the low-reliability region classification based on parameter thresholds. This intermediary acts as a filter that identifies paired data requiring further verification. Paired data falling into this intermediate category (where simple conditions are ambiguous) are then subjected to the more rigorous Mahalanobis distance calculation, ensuring high pairing reliability without significantly impacting processing speed for clear cases.
Data Source
AI summary
There is provided a radar apparatus. An extracting unit extracts a peak signal obtained from a difference frequency between a transmitting signal and a receiving signal during a first period in which the frequency of the transmitting signal ascends and a second period in which the frequency descends. A pairing unit pairs the peak signals of the first and second periods based on a predetermined condition. A deriving unit derives target information including a position of a target based on paired data obtained by pairing the peak signals. The pairing unit selects normal-paired data which is paired in a correct combination, from among the plurality of paired data, based on a plurality of parameter values of the peak signals of the first and second periods which are to be paired, and a discrimination function for discriminating true or false of the pairing.