The Defence Science & Technology Organisation (DSTO), in collaboration with the US Naval Research Laboratory
(NRL), has performed long distance experiments on analogue modulated free space optical links across Chesapeake Bay,
Maryland. In the present work, pulse frequency modulation was used to transmit audio signals over a distance of 32 km
(folded path across the Bay). Still images were transmitted using slow scan television (SSTV) techniques, and a novel
technique to decrease the transmission time of SSTV images is presented.
High-frequency (HF) communications is undergoing resurgence despite advances in long-range satellite communication systems. Defense agencies are using the HF spectrum for backup communications, as well as for spectrum surveillance applications. Spectrum management organizations are monitoring the HF spectrum to control and enforce licensing. These activities usually require systems capable of determining the location of a source of transmissions, separating valid signals from interference and noise, and recognizing signal modulation. Our ultimate aim is to develop robust modulation recognition algorithms for real HF signals, that is, signals propagating by multiple ionospheric modes with cochannel signals and non-Gaussian noise. One aspect of modulation recognition is the extraction of signal identifying features. This paper continues our work of applying various feature parameters to real HF signals and gives guidance on which features show potential for use in robust recognition of HF modulation types in the presence of HF noise and multi-path. It also defines a measure of mean separation distance between modulation types based on an entropy parameter, and discusses the probability density function of HF noise.
High-frequency (HF) communications is undergoing a resurgence despite advances in long-range satellite communication systems. Defense agencies are using the HF spectrum for backup communications as well as for spectrum surveillance applications. Spectrum management organizations are monitoring the HF spectrum to control and enforce licensing. These activities usually require systems capable of determining the location of a source of transmissions, separating valid signals from interference and noise, and recognizing signal modulation. Our ultimate aim is to develop robust modulation recognition algorithms for real HF signals that propagate by multiple ionospheric modes. One aspect of modulation recognition is the extraction of signal identifying features. The most common features for modulation recognition are instantaneous phase, amplitude, and frequency. Many papers present results based on synthetic data and unproven assumptions. However, this paper continues our previous work by applying the coherence function to noisy real HF groundwave signals; which removes the need for synthesized data and unrealistic assumptions.
High-frequency (HF) communications is undergoing resurgence despite advances in long-range satellite communication systems. Defense agencies are using the HF spectrum for backup communications as well as for spectrum surveillance applications. Spectrum management organizations are monitoring the HF spectrum to control and enforce licensing. These activities usually require systems capable of determining the location of a source of transmissions, separating valid signals from interference and noise, and recognizing signal modulation. Our ultimate aim is to develop robust modulation recognition algorithms for real HF signals, that is, signals propagating by multiple ionospheric modes. One aspect of modulation recognition is the extraction of signal identifying features. The most common features for modulation recognition are instantaneous phase, amplitude, and frequency. However, this paper focuses on two feature parameters: coherence and entropy. Signal entropy and the coherence function show potential for robust recognition of HF modulation types in the presence of HF noise and multi-path. Specifically, it is shown that the methods of calculation of coherence and entropy are important and that appropriate calculations ensure stability in the parameters. For the first time a new metric, called Coherence-Median Difference (CMD), is introduced that provides a measure of the dominance of coherence at specific frequencies to coherence at all other frequencies in a particular bandwidth.
KEYWORDS: Modulation, Frequency shift keying, Receivers, Interference (communication), Feature extraction, Signal to noise ratio, Frequency modulation, Phase modulation, Antennas, Signal detection
This paper reviews modulation recognition in the context of HF radio-communications. We investigate entropic distance measures and coherence measures for recognizing HF modulations. Preliminary results shown that it may be possible to identify a modulation and its transmit power level based on the entropic distance between it and another modulation. Coherence estimates may provide characteristic signatures that can be used to identify modulation types.
A critical review of contemporary papers on modulation recognition, signal separation, and Single Station Location (SSL) is described in the context of High-Frequency (HF) radio-communications. High-frequency communications is undergoing resurgence despite advances in long-range satellite communication systems. Defense agencies are using the HF spectrum for backup communications as well as for spectrum surveillance applications. Spectrum management organizations are monitoring the HF spectrum to control and enforce licensing. This type of activity usually requires a system that is able to determine the location of a source of transmissions, separate valid signals from interferers and noise, and characterize signals-of-interest (SOI). The immediate aim is to show that commercial-off-the-shelf (COTS) equipment can be used to locate HF transmission sources, enhance SOIs and reject interference, and recognize signal types. The described work on single-station-location (SSL), signal separation, and modulation recognition is contributing to these goals. This paper describes the overall objectives and some of the disadvantages and benefits of various schemes for single-station-location (SSL), signal separation, and modulation recognition. It also proposes new approaches that may relieve shortcomings of existing methods -- including selection of benchmarks or modulations for various transmission scenarios and propagation modes, and use of multiple digital receivers or compression techniques to improve modulation recognition, signal separation, and location of HF emitters.
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