Abstract:
Electronic Warfare is one of the major deciding factors in the success of conventional and
unconventional warfare. As RF technology is advancing with a very high pace, the conventional
Electronic Warfare equipment are getting obsolete along with. Pakistan Army has indoctrinated a
large quantity of Electronic Warfare equipment and still more is required to compete current
requirement, owing to high tension scenario at borders and operational areas. This high-cost
equipment are prone to frequent upgradation and maintenance as well as being highly resource
dependent. Considering above mentioned issues related to the EW equipment that Pak Army is
using, they are seldom utilized for difficult terrains and border areas and are to be kept as reserve
for conventional warfare. Automatic detection and classification of radio frequency (RF) signals
is a critical task in modern communication systems. [1] With the increasing complexity of wireless
communication systems and the growing demand for spectrum usage, it has become increasingly
important to develop efficient and effective methods for detecting and classifying RF signals. This
paper presents a novel approach for automatic detection of RF signals based on GNU radio
software. The proposed method uses a combination of feature extraction and classification
techniques to identify different types of RF signals. [1]
GNU Radio is an open-source software-defined radio framework that is used to develop signal
processing applications. It provides a range of signal processing blocks that can be used to build
signal processing pipelines. These blocks are used to perform a variety of signal processing tasks,
including filtering, modulation, demodulation, and decoding. To implement automatic detection
and classification of RF signals using GNU Radio, one can use the software to build a signal
processing pipeline that includes blocks for signal acquisition, feature extraction, and
classification. The signal acquisition block can be used to capture RF signals from a radio receiver,
while the feature extraction block can be used to extract relevant features from the captured signals.
These features can include signal frequencies, bandwidth, modulation type and other relevant
parameters.
Key Words: Electronic Warfare, GNU Radio, RF fingerprinting.