Radar Pulse Arrival Date Estimation Using Euclidean Remainders
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Solution Overview
Problem
Radar detectors face challenges in accurately estimating the arrival dates of pulse trains due to close characteristics of radar emitters, limited sensitivity, and high bit rate requirements for data transmission, leading to incorrect sorting and missed pulses.
Innovation Solution
A method that determines the remainder of the Euclidean division of pulse arrival dates by the repetition period and estimates an average arrival date using regression analysis, with steps to eliminate aberrant values and adjust for measurement and estimation errors, allowing for accurate pulse train alignment and reduced data transmission rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar detectors use conventional sorting methods to process pulse trains, then the processing is simple, but the sorting accuracy deteriorates when radar emitter characteristics are close to each other
Solution Approach 1:
The patent replaces conventional mechanical sorting methods with a mathematical approach using least squares regression and Euclidean division to calculate average arrival dates. This substitution enables accurate differentiation between radar emitters with close characteristics by transforming the sorting problem into a computational mathematics problem, thereby improving sorting accuracy without requiring complex hardware modifications.
Solution Approach 2:
The patent changes the parameter used for sorting from direct pulse characteristic comparison to calculated average arrival dates derived from multiple pulses. By computing the average arrival date using least squares regression on the pulse train data, the system transforms the sorting criterion into a more robust parameter that maintains accuracy even when emitter characteristics are similar, thus resolving the contradiction between sorting accuracy and processing complexity.
2Measurement precision
If radar detectors transmit arrival times of all pulses to locate radar transmitters, then the location accuracy is improved, but the data transmission rate increases beyond existing standard links
Solution Approach 1:
The patent extracts only the essential information needed for location accuracy - the average arrival date of the pulse train - while discarding redundant individual pulse arrival time data. By calculating and transmitting only the averaged arrival date rather than all individual pulse times, the system maintains location accuracy through the mathematical representation of pulse train characteristics while dramatically reducing the data transmission rate to compatible levels with existing standard links.
Solution Approach 2:
The patent creates a universal representation of pulse train arrival times through the average arrival date calculation, which serves multiple functions: it maintains the essential location information, reduces data volume for transmission, and provides a standardized format compatible with existing communication links. This multi-functional approach resolves the contradiction by making the data representation adaptable to both accuracy requirements and transmission constraints.
3Measurement precision
If radar detectors operate with limited sensitivity, then the device complexity is reduced, but pulse detection accuracy deteriorates causing missed pulses
Solution Approach 1:
The patent performs preliminary processing by calculating the average arrival date from multiple received pulses before any location determination occurs. This preliminary action aggregates information from multiple pulses, effectively compensating for individual pulse detection limitations. By computing the average across the entire pulse train, the system can maintain detection accuracy even with limited sensitivity, as the aggregation process reinforces valid detections and averages out missed or erroneous individual pulse measurements.
Solution Approach 2:
The patent implements a feedback mechanism where the calculated average arrival date is used to evaluate and adjust the detection process. By comparing the average arrival date against expected values and using the least squares regression to identify and exclude aberrant pulses, the system continuously refines its detection accuracy. This feedback loop allows the detector to compensate for limited sensitivity by iteratively improving the arrival date calculation based on the received pulse data, thereby maintaining measurement precision without requiring high sensitivity hardware.
Data Source
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AI summary
The present invention relates to a method for estimating an average arrival date on a radar detector (9), of a train of pulses emitted by an emitter (8), the radar detector (9) supplying an arrival date for each pulse of the train of pulses and a repetition period of the pulses of the train of pulses, the method comprising the steps of: - determining, for each pulse of the train of pulses, the remainder from the Euclidean division of the arrival date of the pulse by the repetition period of the pulses, and - estimating an average arrival date of the train of pulses from an average of the remainders determined for each pulse.