Radar Pulse Sequence Phase Estimation Under Random Pulse Loss
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Solution Overview
Problem
Existing methods for characterizing radar pulse sequences are hindered by random losses of signal pulses, which distort pulse repetition intervals and affect the accuracy of signal characterization.
Innovation Solution
A method that estimates the pattern repetition period and phase values of radar signals, incorporating a phase histogram analysis to extract peak phases and calculate accurate phase values, even in the presence of random noise, allowing for robust characterization of temporal repetitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse repetition intervals are used to characterize radar pulse sequences, then signal characterization is achieved, but accuracy deteriorates in the presence of random pulse losses
Solution Approach 1:
The patent replaces direct time interval measurement (mechanical approach) with phase-based spectral analysis. Instead of measuring pulse repetition intervals directly in the time domain, the invention transforms the signal to the frequency domain using Fourier transform and extracts phase information from spectral components, making the measurement robust against random pulse losses
Solution Approach 2:
The invention changes the measurement parameter from time domain (pulse repetition intervals) to frequency domain (phase of spectral components). By analyzing the phase of Fourier transform components rather than direct time intervals, the system achieves accurate signal characterization even when pulses are randomly lost
2Reliability
If phase values are extracted from spectral estimation, then robustness against pulse losses is improved, but measurement complexity increases
Solution Approach 1:
The patent uses spectral estimation (Fourier transform) which serves multiple functions simultaneously: it provides frequency analysis for signal characterization and extracts phase information for robust pulse train identification. This multi-functional approach achieves reliability improvement without requiring separate dedicated phase extraction hardware
Solution Approach 2:
The invention introduces spectral components as an intermediary between the raw pulse signal and the final characterization parameters. The Fourier transform creates intermediate frequency-domain representations whose phases contain the required information, simplifying the overall extraction process while improving robustness
Data Source
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AI summary
The invention relates to a method for processing a signal formed of a sequence of pulses, comprising at least one repetitive pattern formed of at least one pulse, said pattern being repeated in the signal with a pattern repetition period. This method comprises the estimation (20) of the pattern repetition period of said signal and the calculation (30), as a function of an arrival date of each pulse with respect to a chosen reference arrival date, and of the estimated pattern repetition period, of a sequence of phases. Thereafter, the method comprises the estimation (60, 70), on the basis of said sequence of calculated phases, of at least one phase value and of an associated standard deviation, said phase value being associated with a phase moment representative of the repetitive pattern, the obtaining (80) and the utilization (90) of parameters characterizing the digital signal by using the estimated phase values.