A novel method for deinterleaving radar signals: First‐order difference curve based on sorted TOA difference sequence

Abstract

Radar signal deinterleaving is used to separate interleaved pulse streams in the electronic support measure (ESM) systems. The histogram methods based on the difference in time of arrival (TOA) are more mature in engineering applications than other methods because of their more effortless implementation. In the increasingly complex electronic battlefield, pulse repetition interval (PRI) jitter, and pulse missing are inevitable in the interleaved pulse stream. The TOA differences of pulse trains with PRI jitter distributes in multiple adjacent PRI bins, which results in the significant reduction of the corresponding histogram value. Furthermore, the histogram values of real PRIs vary with pulse missing, which indicates that the histogram lacks robustness to pulse missing. First-order difference curve based on sorted TOA difference sequence, denoted as FDC-DTOA, is proposed in this paper to overcome the shortcomings mentioned above. In this method, multi-order TOA differences are calculated and then sorted in ascending order. Then, FDC-DTOA is obtained after a first-order backward difference operation. Finally, an adaptive threshold is applied to FDC-DTOA to extract candidate PRIs. The simulation results show that the proposed method has remarkable robustness to pulse missing and excellent performance in deinterleaving the pulse stream with PRI jitter.

A novel deinterleaving method for radar pulse trains using pulse descriptor word dot matrix images and cascade‐recurrent loop network

“…To overcome the problem that the SDIF method lacks robustness when pulses are missing or there is PRI jitter, one of the latest methods, known as the FDCDTOA method proposed by the authors in Ref. [6], first calculates and sorts multi‐level TOA differences, then calculates a first‐order backward difference of those differences to form an FDCDTOA matrix. Finally, the method finds peaks in FDCDTOA to extract candidate PRIs.…”

“…Table 9 shows the accuracy, the quantity of increasing batch and the omission rate of our method and several traditional methods as the number of radars increases. In addition to the classic K ‐Means method and SDIF method, there are also DBSCAN method (preset parameters are eps = 0.2 and minPts = 4), improved the DBSCAN method (preset parameter is minPts = 4, labelled DBSCAN1 in the table) from [8] and FDCDTOA method from [6] used for comparison. For these traditional methods, a group pick step has been added to extract radar with similar PRIs from the sorting results and combine them into a group–group FAR.…”

“…In 2021, Chi [5] used the Limited Penetrable Visibility Graph to build the Construction Complex Network from the radar pulse sequences and then uses the label propagation algorithm and density peak clustering to detect the community structures, which solves the ‘increasing batch’ problem caused by multi‐function radars. In 2022, Xie [6] proposed the first‐order difference curve based on sorted TOA Difference Sequence (FDCDTOA) method, to overcome the problem that the histogram methods lack robustness to problems of missing pulses and of PRI jitter. Traditional methods have gradually improved their performance and successfully overcome numerous challenges.…”

An Improved Sorting Algorithm for Periodic PRI Signals Based on Congruence Transform

“…To overcome the problem of pulse loss, Xie, M. proposed a first-order difference curve based on a sorted TOA difference sequence algorithm (FDC-DTOA) which can suppress harmonics generated by pulse loss. But it has poor sorting ability for complex modulation signals [10]. For the case of missing and short observations, Guo, Q. proposed a radar pulse train de-interleaving method which is particularly suitable for the interleaving of the short and highly interleaved missing pulse train in complex electromagnetic environments.…”

Radar Signal Deinterleaving in Electronic Warfare Systems: A Combined Approach

“…low probability of intercept radars) may prefer transmitting with low power to be invisible in the field or the receiver intercepts the radar pulses at its sensitivity level, which result in missing pulses for the deinterleaving algorithm [11], [28]. All these degradation examples have a great impact on the performance of the deinterleaving algorithm [6], [34] and our article's primary goal is to design a deinterleaving algorithm that can resolve highly complex EW environments.…”