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 loss of pulses, known as scattering, which distorts pulse repetition intervals (PRI) and makes it difficult to accurately determine the pattern repetition period.
Innovation Solution
A method that estimates the pattern repetition period of a signal formed of a sequence of pulses by calculating a sequence of phases and obtaining phase values with associated standard deviations, allowing for robust characterization even with random pulse losses, and involves building a histogram to extract peaks and refine estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pulse repetition intervals are used to characterize radar pulse sequences, then the characterization method is simple, but the accuracy deteriorates due to random pulse losses
Solution Approach 1:
The patent introduces phase values as an intermediary parameter to bridge the relationship between pulse arrival times and pattern repetition period. Instead of directly using pulse repetition intervals which are distorted by pulse losses, the method calculates phase values relative to a reference pattern, which then serve as a more robust basis for estimating the pattern repetition period through histogram analysis.
2Ease of operation
If traditional PRI-based characterization is used, then the method is easy to implement, but reliability deteriorates in the presence of scattering
Solution Approach 1:
The patent transforms the characterization approach by changing from direct PRI measurement to phase value calculation. This parameter transformation makes the characterization more resistant to scattering effects, as phase values are calculated relative to a reference pattern and can accommodate random pulse losses better than absolute PRI measurements.
3Measurement precision
If phase values are calculated for all pulses, then measurement precision improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by focusing computational resources on extracting phase values only for pulses that are part of the repeating pattern, rather than processing all pulses equally. The histogram approach allows identification of dominant phase values corresponding to pattern moments, enabling selective processing that reduces overall computational complexity while maintaining precision for the critical pattern characterization.
Data Source
AI summary
A method for processing a signal formed of a sequence of pulses, including at least one repetitive pattern formed of at least one pulse, the pattern being repeated in the signal with a pattern repetition period, the method including estimating the pattern repetition period of the signal and calculating, as a function of (i) an arrival date of each pulse with respect to a chosen reference arrival date, and (ii) the estimated pattern repetition period, a sequence of phases; thereafter, the method includes estimating, on the basis of the calculated sequence of phases, at least one phase value and an associated standard deviation, the phase value being associated with a phase moment representative of the repetitive pattern, and obtaining and utilizing parameters characterizing the digital signal by using the estimated phase values.