• Journal of Satellite, Information and Communications
• /
• v.8 no.4
• /
• pp.159-163
• /
• 2013

In this paper, we propose a new method to deinterleave multi-stage stagger PRI signals of pulse radars using the electronic intelligence systems. While former algorithms were based on hardware PRI tracker only using the first deviation of the TOA of radar signals, this paper uses the first and the second deviation of TOA of radar signals and uses the PRI histogram method to deinterleave multiple PRIs of pulse radars. This algorithm can be used for deinterleaving various PRI signals at electronic intelligence systems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.8
• /
• pp.673-681
• /
• 2002

This paper presents a new algorithm for estimating pulse repetition intervals (PRIs) of stagger PRI pulse trains using a 2 dimensional TDOA histogram. The PRI transform algorithm can remove harmonics of stable and jitter PRI pulse trains in a TDOA histogram. But, it is impossible for the algorithm to detect stagger PRI pulse trains because it regards frame PRIs of stagger Pulse trains as harmonics of stable PRI pulse trains. A new algorithm of this paper has an ability to distinguish stagger pulse trains from harmonics of other pulse trains and to estimate frame PRIs of detected pulse trains.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.11
• /
• pp.5372-5378
• /
• 2012

In this paper, we propose a new method to quickly deinterleave the stagger PRI signals and D&S(Dwell and Switch) PRI signals from the EP radar using the electronic warfare system. While former algorithms were based on stochastic methods only using the first deviation of the TOA of radar signals, this paper uses the first and the second deviation of the TOA of radar signals to deinterleave multiple PRIs of EP radars. When we simulate multiple PRIs of EP radars and test the simulated radar signals using the proposed algorithm, various PRI signals such as fixed, jitter, D&S and stagger PRI are well deinterleaved in a short time. This algorithm is found to be very useful for electronic warfare systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.775-778
• /
• 2016

In this paper, we propose a new method to automatically recognize PRI modulation type of radar signal at ES(Electronic Support) in electronic singal environment. The propose method stores pattern of PRI(Pulse Repetition Interval) of radar signal and uses statistic data, which firstly classifies into 2 classes. Then the proposed method recognizes each PRI signal using statistic characteristic of PRI. We apply various 5 kinds of PRI signal such as constant PRI, jitter PRI, D&S(dwell & switch) PRI, stagger PRI, sliding PRI, etc. The result shows the proposed method correctly identifies various PRI signals.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.3
• /
• pp.34-41
• /
• 2014

Through applying hostile radar signals that use stagger PRI to PRI transform in real time, we can analyze stagger PRI and calculate the future TOA for active cancellation by using measured TOA and estimated PRI. We shows the effect of the errors that are contained in PRI and measured TOA. Then, it will suggest the technique to improve the accuracy of estimated PRI and the TOA averaging method for reducing the effect of measured TOA error. Finally, we will show that accuracy of estimated future TOA that is calculated by proposed scheme is higher than that of future TOA that is simply calculated with TDOA and newest TOA through comparing RMSE performance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.7
• /
• pp.1536-1541
• /
• 2009

In this paper, we present a novel pulse train identification method for two step stagger pulse train. Generally radar uses a fixed pulse train, and it is easy for electronic warfare system to measure the pulse repeat interval(PRI) and identify the radar. But it is very difficult to measure the PRI of stagger pulse radar because the pulse interval is periodically changed. We suggest a novel method to measure the PRI and identify the radars using the second deviation of pulse train. This method is faster comparing with Histogram method. We have a good PRI measurement results for 2 step stagger signals.

• Journal of Convergence for Information Technology
• /
• v.8 no.5
• /
• pp.137-143
• /
• 2018

Generally, a radar signal is modulated and transmitted in order to avoid signal detection. In electronic warfare, the specification of a radar is recognized by analysing the received radar pulses. In this paper, we propose an algorithm to recognize the PRI (Pulse Repetition Interval) type of radar signals. This algorithm uses the autocorrelation technique applying different comparison ranges according to the PRI type. It applies a short comparison window to stable and staggered PRI, and a relatively large comparison range to jittered PRI. The experiment shows that the proposed algorithm can discriminate the PRI type of radar pulses correctly. For the more, it can find out the stagger level of staggered type of radar signals.

• Journal of Convergence for Information Technology
• /
• v.10 no.12
• /
• pp.31-38
• /
• 2020

Radar signal identification of electronic warfare is a technology that recognizes the pulse repetition interval (PRI) from a set of pulse description words (PDWs) generated by the signal receiver. Conventionally batch processing is widely used in which a number of PDWs are collected as a unit and identifies PRI from the batch. In this paper, we propose a feature extraction algorithm based on the streaming process. This technique does not wait to form a batch. Whenever a PDW(Pulse Description Word) is generated from the signal receiver, the streaming process tries to form a cluster of PDWs, and makes the DTOA (Difference of Time of Arrival) histogram, finds out the frame PRI based on the concentration ratio, and decides the number of stagger stages. Experiments proved that the proposed algorithm derives stable recognition results as the cluster size increases.