Automotive Access Pattern Detection Reducing False Alarms
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Solution Overview
Problem
Current pattern detection systems in automotive access systems face challenges with high false alarm rates and reduced sensitivity due to noise interference, especially when using short target patterns, which affects battery life and system reliability.
Innovation Solution
The proposed data-receiving circuit incorporates a pattern detection unit with a correlator that compares the input signal to multiple sample-sets, allowing for exact and inexact matches, reducing false alarms by increasing the number of required matches and adjusting thresholds, thereby improving sensitivity and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a short target pattern is used for pattern detection, then the detection speed is improved, but the false alarm rate increases and sensitivity decreases
Solution Approach 1:
The pattern detection process is segmented into multiple independent sample-sets, where each sample-set contains multiple samples. Instead of detecting based on a single pattern match, the system divides the detection into multiple samples within each set and evaluates multiple sample-sets, thereby maintaining short pattern length while reducing false alarms through statistical validation across segments.
Solution Approach 2:
The system requires a predetermined number of sample-sets (e.g., 2 or more) to match the target pattern before confirming detection. This excessive action of requiring multiple matches beyond a single pattern comparison reduces the false alarm rate while maintaining detection speed, as the additional validation steps are efficiently processed through parallel sample evaluation.
2Speed
If a short target pattern is used for pattern detection, then the detection speed is improved, but the sensitivity decreases
Solution Approach 1:
Multiple samples within each sample-set are merged to form a collective detection result. The system combines the information from multiple samples in a sample-set and across multiple sample-sets, allowing short patterns to maintain high sensitivity by aggregating evidence from multiple measurements rather than relying on a single pattern comparison.
Solution Approach 2:
The system uses feedback from multiple sample-sets to validate detection results. Each sample-set provides feedback on pattern matching, and the cumulative feedback from multiple sample-sets enhances sensitivity by confirming detections through repeated validation, ensuring that short patterns do not sacrifice measurement precision.
3Reliability
If the number of required matches is increased to reduce false alarms, then the false alarm rate decreases, but the power consumption increases
Solution Approach 1:
The system performs preliminary evaluation of samples within sample-sets before committing to full pattern verification. By pre-processing and初步 evaluating the samples, the system can quickly identify and discard non-matching sample-sets without consuming full power, thereby requiring multiple matches for false alarm reduction while minimizing energy consumption through early rejection of invalid candidates.
Data Source
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AI summary
The disclosure relates to pattern detection unit 200 and associated method. The unit 200 comprises a shift register 202 configured to over-sample a multi-bit input signal such that each bit of the input signal is represented by a plurality of samples in the shift register 202; and a correlator 204 configured to compare a target pattern with two or more sample-sets, each sample-set comprising a corresponding sample from each of the plurality of samples of each bit, and classify each compared sample-set as one of: an exact match; an inexact match; or a non-match to the target pattern in order to determine whether or not the input signal matches the target pattern.