• 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.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.7
• /
• pp.85-91
• /
• 2016

Typically, radar systems change the pulse repetition interval of their modulated signal in order to avoid detection. On the other hand the radar-signal detection system tries to detect the modulation pattern. The histogram or auto-correlation methods are usually used to detect the PRI pattern of the radar signal. However these methods tend to lost the sequence information of the PRI pulses. This paper proposes a PRI-sequence detection algorithm based on the finite-state machine that could detect not only the PRI pattern but also their sequence.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.10
• /
• pp.137-144
• /
• 2014

The Electronic Support System collects and analyzes the received radar signals in order to cope with the electronic attack in real-time. The radar-pulse clustering system classifies the radar signals that are considered to be emitted by a single source. This paper proposed a radar-pulse clustering algorithm based on four kinds of features: the direction, frequency, pulse width, and the difference of arrival time between two successive pulses. The experiment results show that the proposing algorithm could trace the moving emitter and classify the timely separated signals into different classes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.12
• /
• pp.1100-1107
• /
• 2015

In this paper, we propose an algorithm to identify Wobble PRI and Sinusoidal PRI among Radar pulses. We applied not only the DTOA(Difference Time Of Arrival) concept of radar pulse signals incoming to antennas but also a rising and falling cub characteristic of those PRIs. After making a program by such algorithm, we input each 40 data to Wobble PRI's and Sinusoidal PRI's identification programs and in result, those programs fully processed the data the according to expectations. In the future, those programs can be applied to the ESM, ELINT system.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.6
• /
• pp.611-619
• /
• 2016

Success in modern war depends on electronic warfare. Therefore, It is very important to identify the kind of Radar PRI modulations in a lot of Radar electromagnetic waves. In this paper, I propose an algorithm to identify Linear up Sliding PRI, Non-Linear up Sliding PRI and Linear Down Sliding PRI, Non-Linear Down Sliding PRI among many Radar pulses. We applied not only the TDOA(Time Difference Of Arrival) concept of Radar pulse signals incoming to antennas but also a rising and falling curve characteristics of those PRI's. After making a program by such algorithm, we input each 40 data to those PRI's identification programs and as a result, those programs fully processed the data in according to expectations. In the future, those programs can be applied to the ESM, ELINT system.