Modulation parameter estimation of LFM interference for direct sequence spread spectrum communication system in alpha-stable noise

The linear frequency modulation (LFM) interference is one of the typical broadband interferences in direct sequence spread spectrum (DSSS) communication system. In this article, a novel modulation parameter estimation method of LFM interference is proposed for the DSSS communication system in alpha-stable noise. To accurately estimate the modulation parameters, the alpha-stable noise should be eliminated first. Thus, we formulate a new generalized extended linear chirplet transform to suppress the alpha-stable noise, for a robust time-frequency, transformation of LFM interference is realized. Then, using the Radon transform, the maximum value after transformation and the chirp rate according to the angle related to the maximum value are estimated. In addition, a generalized Fourier transform is introduced to estimate the initial frequency of the LFM interference. For the performance analysis, the Cramér-Rao lower bounds of the estimated chirp rate and the initial frequency of the LFM interference in the presence of alpha-stable noise are derived. Moreover, the asymptotic properties of the modulation parameter estimator are analyzed. Simulation results demonstrate that the performance of the proposed parameter estimation method significantly outperforms existing methods, especially in a low SNR regime

Time-frequency represetation of radar signals using Doppler-Lag block searching Wigner-Ville distribution

Radar signals are time-varying signals where the signal parameters change over time. For these signals, Quadratic Time-Frequency Distribution (QTFD) offers advantages over classical spectrum estimation in terms of frequency and time resolution but it suffers heavily from cross-terms. In generating accurate Time-Frequency Representation (TFR), a kernel function must be able to suppress cross-terms while maintaining auto-terms energy especially in a non-cooperative environment where the parameters of the actual signal are unknown. Thus, a new signal-dependent QTFD is proposed that adaptively estimates the kernel parameters for a wide class of radar signals. The adaptive procedure, Doppler-Lag Block Searching (DLBS) kernel estimation was developed to serve this purpose. Accurate TFRs produced for all simulated radar signals with Instantaneous Frequency (IF) estimation performance are verified using Monte Carlo simulation meeting the requirements of the Cramer-Rao Lower Bound (CRLB) at SNR > 6 dB

TS-MUWSN: Time synchronization for mobile underwater sensor networks

Time synchronization is an important, yet challenging, problem in underwater sensor networks (UWSNs). This challenge can be attributed to: 1) messaging timestamping; 2) node mobility; and 3) Doppler scale effect. To mitigate these problems, we present an acoustic-based time-synchronization algorithm for UWSN, where we compare several message time-stamping algorithms in addition to different Doppler scale estimators. A synchronization system is based on a bidirectional message exchange between a reference node and a slave one, which has to be synchronized. Therefore, we take as reference the DA-Sync-like protocol (Liu et al., 2014), which takes into account node's movement by using first-order kinematic equations, which refine Doppler scale factor estimation accuracy, and result in better synchronization performance. In our study, we propose to modify both time-stamping and Doppler scale estimation procedures. Besides simulation, we also perform real tests in controlled underwater communication in a water test tank and a shallow-water test in the Mediterranean Sea.Peer ReviewedPostprint (author's final draft