Performances enhancement of underwater wireless optical communications (UWOC) using pulse position modulation

In this work, we study the performance analysis of underwater optical wireless communication (UOWC) transmission link by incorporating optical code division multiple access (OCDMA) using pulse position modulation (PPM) to enhance the channel range and cardinality. Bit error rate (BER) variations are examined versus the range, modulation type (on–off keying (OOK), quadrature amplitude modulation (QAM), etc.), number of users as well as the channel attenuation caused by different water types. The power and transmitter inclination angle limitation, of the enhanced system, are also presented in order to determine the threshold for which the minimum BER 10−9 is achievable.

An Intra-Pulse Modulation Type Recognition Algorithm for Radar Signals Based on the Improved Residual Network

For purpose of solve the problem of poor discrimination and robustness of intra-pulse signal features extracted by the traditional methods, this paper proposes a radar signal intra-pulse modulation type recognition algorithm based on the improved residual network. Firstly, one-dimensional time-domain radar signal is converted into two-dimensional time-frequency image by Smoothing Pseudo Wigner-Ville Distribution; Then the time-frequency image is preprocessed; ResNet-50 network is chosen as the framework. In order to retain the feature map information as much as possible, the convolution kernel is increased in the residual module. The cross entropy loss function and the center loss function are used as the loss function to speed up the convergence of the network. The improved residual network is used to realize the intra-pulse modulation type recognition of radar signal. The simulation experiments show that when the SNR is -14dB, the overall average recognition accuracy of the improved algorithm for eight kinds of radar signals (CM, LFM, NLFM, BLFM, BPSK, QPSK, OPSK, LFM+BPSK) can reach 97.29%, which shows the effectiveness.

Intelligent Recognition of Chirp Radar Deceptive Jamming Based on Multi-Pulse Information Fusion

The perception of jamming types is very important for protecting our radar in complex electromagnetic environments. Radar active deceptive jamming based on digital radio frequency memory (DRFM) has a high coherence with the target echo, which confuses the information of the target echo and achieves the effect of hiding the real target. Traditional deceptive jamming recognition methods need to extract complex features and artificially set classification thresholds, which is inefficient. The existing neural network-based jamming identification methods still follow the pattern of signal modulation-type identification, so there are fewer types of jamming that can be identified, and the identification accuracy is low in the case of low jamming-to-noise ratios (JNR). This paper studies the input of jamming recognition networks and proposes an improved intelligent identification method for chirp radar deceptive jamming. This method fuses three short-time Fourier transform time–frequency graphs disturbed by three consecutive pulse periods into a new graph as the input of the convolutional neural network (CNN). Using a CNN to classify the time–frequency image has realized the recognition of a variety of common deceptive jamming techniques. Similarly, by changing the network input, the original signal is used to replace the echo signal, which improves the accuracy of the jamming recognition in the case of a low JNR.

A Wireless Covert Channel Based on Dirty Constellation with Phase Drift

Modern telecommunications systems require the use of various transmission techniques, which are either open or hidden. The open transmission system uses various security techniques against its unauthorized reception, and cryptographic solutions ensure the highest security. In the case of hidden transmissions, steganographic techniques are used, which are based on the so-called covert channels. In this case, the transparency and stealth of the transmission ensure its security against being picked up by an unauthorized user. These covert channels can be implemented in multimedia content, network protocols, or physical layer transmissions. This paper focuses on wireless covert channels. We present a novel method of steganographic transmission which is based on phase drift in phase-shift keying or quadrature amplitude modulation (QAM) and is included in the so-called dirty constellation techniques. The proposed approach is based on the drift correction modulation method, which was previously used in the watermarking of audio-signals. The developed solution is characterized by a variable bit rate, which can be adapted to the used modulation type and transmission conditions occurring in radio channels. In the paper, we present the method of generating and receiving hidden information, simulation research, and practical implementation of the proposed solution using the software-defined radio platform for selected QAM.

FPGA based Identification of Frequency and Phase Modulated Signals by Time Domain Digital Techniques for ELINT Systems

In this paper, a decision tree algorithm based on time-domain digital technique is developed for the identification and classification of diverse radar intra-pulse modulated signals for the electronic intelligence system in real-time. This includes linear frequency modulation, non-linear frequency modulation, stepped frequency modulation and bi-phase modulation. The received signal is digitised and the instantaneous phase and high accuracy instantaneous frequency are estimated. The instantaneous amplitude is also estimated to get the start and stop of the pulse. Instantaneous parameters are estimated using a moving autocorrelation technique. The proposed algorithm is employed on the instantaneous frequency and the modulation is identified. The modulation type and modulation parameter are important for unique radar identification when similar radars are operating in a dense environment. Simulations are carried out at various SNR conditions and results are presented. The model for algorithm is developed using a system generator and implemented in FPGA. These results are compared when the proposed algorithm is used with the existing digital in-phase and quadrature-phase (DIQ) technique of instantaneous frequency and amplitude estimation.

Modeling of Aircraft and RPAS Data Transmission via Satellites

This chapter is devoted to the modeling of aircraft data transmission via low-orbit satellites. Satellite communication channel models were designed, which allow to investigate BER dependencies on the type of signal modulation, information transfer rate, signal power, antenna diameters, and nonlinearity of a high power amplifier. Impact of a modulation type (BPSK, QPSK, 8PSK, 16QAM), Eb / N0, satellite transponder amplifier gain without and with coding on a BER was investigated. Effectiveness of error detection and correction was analyzed using classic linear block and convolutional codes. Free space path loss, AWGN, and radio frequency satellite channels were considered. MIMO 2 × 1 and 3 × 2 fading uplink/downlink channels with antenna diversity were analyzed. Results were compared with AWGN uplink/downlink channels. On the base of these models, channels integrity was investigated.