17-03-2014, 06:13 PM
Abstract—In a dense modern electronic warfare environment,
there are a lot of radar signals. The identification of these
radar signals is the main task of the electronic support
measures systems. Pulse repetition intervals of signals received
from radars can have various PRI modulations and levels. In
this paper, a new method of recognizing PRI modulation type
and its levels is proposed for ESM systems. The proposed
method is based not only on the properties of the biased
autocorrelation function of the PRI sequences but also on the
development of a hierarchical clustering method for both
classifying PRI modulation types and clustering the PRI levels.
The performance of the proposed method has also been
evaluated in a simulation scenario.
Keywords- Biased autocorrelation function; electronic
support measures; PRI modulation; time of arrival
I. INTRODUCTION
An electronic support measures (ESM) system receives
signals from many radar sources with various parameters. A
pulsed-radar system uses specified parameters to transmit its
signal. As shown in Fig. 1 measured parameters include time
of arrival (TOA), pulse width (PW), radio frequency (RF),
pulse amplitude (PA) and angle of arrival (AOA). As the
radars are developing, they use more complicated pulse
repetition interval (PRI) modulations to have multiple
purposes and to hide from ESM systems. Therefore, it is
important to develop the ESM systems which have duty of
recognizing active radars in the environment. By using PRI
modulation recognition in ESM systems, the process of
recognizing the radars can be developed.
Common types of PRI modulation are constant, jittered,
staggered, sliding, wobulated and DS (Dwell and Switch). In
conventional methods, constant and staggered PRI
modulations are recognized in pulse de-interleaving process
[2]. But the other PRI modulation types are reported as
complicated modulation types or classified as noise [5]. In
[1] it is assumed that constant and staggered PRI modulation
types are extracted in pulse de-interleaving process by CDIF
or SDIF methods [3, 4, 7], then complicated PRI modulation
types are recognized by autocorrelation function properties.
Usually pulse de-interleaving is processed by clustering the
RF, AOA and PW pulse parameters. Then TOAs of each
cluster are used to recognize the PRI modulation type and
determine the PRI levels.
In this paper, MSE estimation for mean PRI is calculated.
The mathematical definitions of PRI modulation types and
their specifications are presented. Then a hierarchical
clustering method is introduced to determine the PRI levels
and is used in recognition of PRI modulation types. Next, the
procedure of PRI modulation recognition is proposed. To
show the performance of the presented method, it has been
evaluated in a simulation scenario in section VI.
there are a lot of radar signals. The identification of these
radar signals is the main task of the electronic support
measures systems. Pulse repetition intervals of signals received
from radars can have various PRI modulations and levels. In
this paper, a new method of recognizing PRI modulation type
and its levels is proposed for ESM systems. The proposed
method is based not only on the properties of the biased
autocorrelation function of the PRI sequences but also on the
development of a hierarchical clustering method for both
classifying PRI modulation types and clustering the PRI levels.
The performance of the proposed method has also been
evaluated in a simulation scenario.
Keywords- Biased autocorrelation function; electronic
support measures; PRI modulation; time of arrival
I. INTRODUCTION
An electronic support measures (ESM) system receives
signals from many radar sources with various parameters. A
pulsed-radar system uses specified parameters to transmit its
signal. As shown in Fig. 1 measured parameters include time
of arrival (TOA), pulse width (PW), radio frequency (RF),
pulse amplitude (PA) and angle of arrival (AOA). As the
radars are developing, they use more complicated pulse
repetition interval (PRI) modulations to have multiple
purposes and to hide from ESM systems. Therefore, it is
important to develop the ESM systems which have duty of
recognizing active radars in the environment. By using PRI
modulation recognition in ESM systems, the process of
recognizing the radars can be developed.
Common types of PRI modulation are constant, jittered,
staggered, sliding, wobulated and DS (Dwell and Switch). In
conventional methods, constant and staggered PRI
modulations are recognized in pulse de-interleaving process
[2]. But the other PRI modulation types are reported as
complicated modulation types or classified as noise [5]. In
[1] it is assumed that constant and staggered PRI modulation
types are extracted in pulse de-interleaving process by CDIF
or SDIF methods [3, 4, 7], then complicated PRI modulation
types are recognized by autocorrelation function properties.
Usually pulse de-interleaving is processed by clustering the
RF, AOA and PW pulse parameters. Then TOAs of each
cluster are used to recognize the PRI modulation type and
determine the PRI levels.
In this paper, MSE estimation for mean PRI is calculated.
The mathematical definitions of PRI modulation types and
their specifications are presented. Then a hierarchical
clustering method is introduced to determine the PRI levels
and is used in recognition of PRI modulation types. Next, the
procedure of PRI modulation recognition is proposed. To
show the performance of the presented method, it has been
evaluated in a simulation scenario in section VI.