Sensors and Systems for the Detection of Explosive Devices - An Overview: The paper presents analyses of current research projects connected with explosive material sensors. Sensors are described assigned to X and γ radiation, optical radiation sensors, as well as detectors applied in gas chromatography, electrochemical and chemical sensors. Furthermore, neutron techniques and magnetic resonance devices were analyzed. Special attention was drawn to optoelectronic sensors of explosive devices.

This article aims to propose an algorithm for the automatic recognition of selected radar signals. The algorithm can find application in areas such as Electronic Warfare (EW), where automatic recognition of the type of intra-pulse modulation or the type of emitter operation mode can aid the decision-making process. The simulations carried out included the analysis of the classification possibilities of linear frequency modulated pulsed waveform (LFMPW), stepped frequency modulated pulsed waveform (SFMPW), phase coded pulsed waveform (PCPW), rectangular pulsed waveforms (RPW), frequency modulated continuous wave (FMCW), continuous wave (CW), Stepped Frequency Continuous Wave SFCW) and Phase Coded Continuous Waveform (PCCW). The algorithm proposed in this paper is based on the use of continuous wavelet transform (CWT) coefficients and higher-order statistics (HOS) in the feature determination of selected signals. The Principal Component Analysis (PCA) method was used for dimensionality reduction. An artificial neural network was then used as a classifier. Simulation studies took into account the presence of noise interference with signal-to-noise ratio (SNR) in the range from −5 to 10 dB. Finally, the obtained classification efficiency is presented in the form of a confusion matrix. The simulation results show a high recognition test accuracy, above 99% with a signal-to-noise ratio greater than 0 dB. The article also deals with the selection of the type and parameters of the wavelet. The authors also point to the problems encountered during the research and examples of how to solve them.

Details var a2a_config = a2a_config || {}; a2a_config.onclick = 1; a2a_config.locale = "pl"; a2a_config.color_main = "D7E5ED"; a2a_config.color_border = "9D9D9D"; a2a_config.color_link_text = "ffffff"; a2a_config.color_link_text_hover = "ffffff"; a2a_config.color_bg = "d9d9d9"; a2a_config.icon_color = "#4e4e4e"; a2a_config.exclude_services = ["dihitt", "delicious", "whatsapp", "dzone", "sms", "stumpedia", "viber", "yahoo_messenger", "google_plus"]; Details PDF BIBTEX RIS Title Specific emitter identification based on graphical representation of the distribution of radar signal parameters Journal title Bulletin of the Polish Academy of Sciences: Technical Sciences Yearbook 2015 Volume 63 Issue No 2 Authors Dudczyk, J. ; Kawalec, A. Divisions of PAS Nauki Techniczne Coverage 391-396 Date 2015[2015.01.01 AD - 2015.12.31 AD] Identifier DOI: 10.1515/bpasts-2015-0044 ; ISSN 2300-1917 Source Bulletin of the Polish Academy of Sciences: Technical Sciences; 2015; 63; No 2; 391-396

Automatic modulation recognition plays a vital role in electronic warfare. Modern electronic intelligence and electronic support measures systems are able to automatically distinguish the modulation type of an intercepted radar signal by means of real-time intra-pulse analysis. This extra information can facilitate deinterleaving process as well as be utilized in early warning systems or give better insight into the performance of hostile radars. Existing modulation recognition algorithms usually extract signal features from one of the rudimentary waveform characteristics, namely instantaneous frequency (IF). Currently, there are a small number of studies concerning IF estimation methods, specifically for radar signals, whereas estimator accuracy may adversely affect the performance of the whole classification process. In this paper, five popular methods of evaluating the IF–law of frequency modulated radar signals are compared. The considered algorithms incorporate the two most prevalent estimation techniques, i.e., phase finite differences and time-frequency representations. The novel approach based on the generalized quasi-maximum likelihood (QML) method is also proposed. The results of simulation experiments show that the proposed QML estimator is significantly more accurate than the other considered techniques. Furthermore, for the first time in the publicly available literature, multipath influence on IF estimates has been investigated.