David Bonacci

CRC-assisted error correction in a trellis coded system with bit stuffing

This paper introduces a new error correction strategy using cyclic redundancy checks (CRC) for a trellis coded system in the presence of bit stuffing. The proposed receiver is designed to simultaneously demodulate, decode and correct the received message in the presence of bit stuffing. It is based on a Viterbi algorithm exploiting the conditional transitions of an appropriate extended trellis. The receiver is evaluated with automatic identification system (AIS) messages constructed with a 16 bit CRC and a Gaussian Minimum Shift Keying (GMSK) modulation. The stuffed bits are inserted after any sequence of five consecutive bits 1 as requested by the AIS recommendation. Simulation results illustrate the algorithm performance in terms of packet error rate. A gain of more than 2.5dB is obtained when compared to the conventional GMSK receiver.

Improving frequency resolution for correlation-based spectral estimation methods using subband decomposition

Subband decomposition has already been shown to increase the performance of spectral estimators, but induced frequency overlapping may be troublesome, bringing edge effects at subband borders. A recent paper (Bonacci, D. et al., EUSIPCO, 2002) proposed a method (SDFW - subband decomposition and frequency warping) allowing subband decomposition to be performed without aliasing. We modify this subband decomposition in order to improve frequency resolution for any correlation based spectral estimator when applied to the subband outputs. Three main improvements are proposed: the subband decomposition is based on comb filters; the SDFW method warping operation is performed using a complex frequency modulation; the autocorrelation is estimated using all sub-series from each subband. Simulation results demonstrate the anticipated performance of the proposed method.

Joint phase-recovery and demodulation-decoding of AIS signals received by satellite

This paper presents a demodulation algorithm for automatic identification system (AIS) signals received by a satellite. The main contribution of this work is to consider the phase recovery problem for an unknown modulation index, coupled with a time-varying phase shift. The proposed method is based on a demodulator introduced in a previous paper based on a Viterbi-type algorithm applied to an extended trellis. The states of this extended trellis are composed of a trellis-code state and of a cyclic redundancy check state. The bit stuffing mechanism is taken into account by defining special conditional transitions in the extended trellis. This algorithm estimates and tracks the phase shift by modifying the Euclidean distance used in the trellis. Simulation results obtained with and without phase tracking are presented and compared in the context of the AIS system.

Cyclic redundancy check-based detection algorithms for automatic identification system signals received by satellite

This paper addresses the problem of demodulating signals transmitted in the automatic identification system. The main characteristics of such signals consist of two points: (i) they are modulated using a trellis-coded modulation, more precisely a Gaussian minimum shift keying modulation; and (ii) they are submitted to a bit stuffing procedure, which makes more difficult the detection of the transmitted information bits. This paper presents several demodulation algorithms developed in different contexts: mono-user and multi-user transmissions, and known/unknown phase shift. The proposed receiver uses the cyclic redundancy check (CRC) present in the automatic identification system signals for error correction and not for error detection only. By using this CRC, a particular Viterbi algorithm, on the basis of a so-called extended trellis, is developed. This trellis is defined by extended states composed of a trellis code state and a CRC state. Moreover, specific conditional transitions are defined to take into account the possible presence of stuffing bits. The algorithms proposed in the multi-user scenario present a small increase of computation complexity with respect to the mono-user algorithms. Some performance results are presented for several scenarios in the context of the automatic identification system and compared with those of existing techniques developed in similar scenarios.

Extended constrained Viterbi algorithm for AIS signals received by satellite

This paper addresses the problem of error correction of AIS messages by using the a priori knowledge of some information in the messages. Indeed, the AIS recommendation sets a unique value or a range of values for certain fields in the messages. Moreover, the physics can limit the range of fields, such as the speed of the vessel or its position (given the position of the receiver). The repetition of the messages gives also some information. Indeed, the evolution of the ship position is limited between messages and the ship ID is known. The constrained demodulation algorithm presented in this article is an evolution of the constrained Viterbi algorithm (C-VA). It is based on a modified Viterbi algorithm that allows the constraints to be considered in order to correct transmission errors by using some new registers in the state variables. The constraints can be either a single value or a range of values for the message fields. Simulation results illustrate the algorithm performance in terms of bit error rate and packet error rate. The performance of the proposed algorithm is 2 dB better than that obtained with the receiver without constraints.

Lowpass/bandpass signal reconstruction and digital filtering from nonuniform samples

This paper considers the problem of non uniform sampling in the case of finite energy functions and random processes, not necessarily approaching to zero as time goes to infinity. The proposed method allows to perform exact signal reconstruction, spectral estimation or linear filtering directly from the non-uniform samples. The method can be applied to either lowpass, or bandpass signals.

PARTIAL CRC-ASSISTED ERROR CORRECTION OF AIS SIGNALS RECEIVED BY SATELLITE

This paper deals with the demodulation of automatic identification system (AIS) signals received by a satellite. More precisely, an error correction algorithm is presented, whose computational complexity is reduced with respect to that of a previously considered approach. This latter approach makes use of the cyclic redundancy check (CRC) of a message as redundancy, in order to correct transmission errors. In this paper, the CRC is also considered as a correction tool, but only a part of it is used for that purpose; the remaining part is only used as an error detection means. This novel approach allows the decoding performance to be adapted to the noise power, and provides a reduction of the computational complexity. Simulation results obtained with and without complexity optimization are presented and compared in the context of the AIS system.

Wireless technologies pre-screening: Evaluation for avionics

This paper presents the recent results of SCA project (communication systems for avionics), on the evaluation of the means of communication able to ensure airlines companies needs on airport platforms. Exchange of AOC/AAC (aeronautical operational control/aeronautical administrative communication) messages between aircrafts and their airline companies is required on the ground. The concept of technology readiness level is presented to lead to the best choice of wireless technology. Evaluation of each technology is described for various scenarios of aircraft location within the airport.

Improving subband spectral estimation using modified AR model

It has already been shown that spectral estimation can be improved when applied to subband outputs of an adapted filterbank rather than to the original fullband signal. In the present paper, this procedure is applied jointly to a novel predictive autoregressive (AR) model. The model exploits time-shifting and is therefore referred to as time-shift AR (TS-AR) model. Estimators are proposed for the unknown TS-AR parameters and the spectrum of the observed signal. The TS-AR model yields improved spectrum estimation by taking advantage of the correlation between subseries that arises after decimation. Simulation results on signals with continuous and line spectra that demonstrate the performance of the proposed method are provided.

Ship detection using SAR and AIS raw data for maritime surveillance

This paper studies a maritime vessel detection method based on the fusion of data obtained from two different sensors, namely a synthetic aperture radar (SAR) and an automatic identification system (AIS) embedded in a satellite. Contrary to most methods widely used in the literature, the present work proposes to jointly exploit information from SAR and AIS raw data in order to detect the absence or presence of a ship using a binary hypothesis testing problem. This detection problem is handled by a generalized likelihood ratio detector whose test statistics has a simple closed form expression. The distribution of the test statistics is derived under both hypotheses, allowing the corresponding receiver operational characteristics (ROCs) to be computed. The ROCs are then used to compare the detection performance obtained with different sensors showing the interest of combining information from AIS and radar.