Search

In this paper, we propose an automatic supervised classification of objects lying on the sea floor or buried in sediment layers. This pattern recognition provides a way to distinguish natural and manufactured objects and then should be helpful to detect mine, pipe-line, or wreckage. Proposed methods combine different techniques: pattern information extraction, relevant parameter search, and supervised classifier. Parameters are automatically selected using a principal component analysis to reduce misclassification rate and to simplify classifier structure. Performances of different parameters (two-dimensional and three-dimensional) are compared and discussed from testing on synthetic and real data bases.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in an uncertain environment with obstacles. The proposed strategy consists in separating the path planning from the control algorithm. The path planning is done by computing the time optimal collision-free trajectory which takes into account the limitations on the linear and angular speeds of the vehicle. The position and shape of obstacles are computed by a vision algorithm using a single camera. A saturated controller based on integral sliding mode is designed to solve the tracking problem in the presence of input saturations and of the unknown disturbances. The effectiveness, perfect performance of obstacle avoidance, real-time and high robustness properties are demonstrated by experimental results.

Adaptive modulation techniques (bit/power- loading) allow great optimisation of spectral efficiency, power consumption and error rates in wireless multicarrier systems. However, multicast transmissions complicate their implementation as there is no longer one single channel to optimize the transmission for. In this paper, a new approach to loading for OFDM on wireless multicast systems is proposed. We show that a great performance enhancement can be expected in ideal conditions. After deriving an upper bound for the error rate in these conditions, we study the performance degradation occurring with imperfect channel state information.

International audience; With the rising number of modulation types used in multiuser communication systems, we need to find efficient methods to discriminate them. Indeed, modulation recognition has become important in wireless communications for both civilian and military applications. Traditionally, to classify modulation types, most studies assume abundant a priori knowledge about modulated signals such as binary data rate, baud rate or carrier frequency. However, new transmission receiver systems need to classify automatically digital modulations without specific information. In the course of making decision on modulation type, these parameters may have to be estimated in order to perform efficient demodulation. This paper proposes a new way of estimating baud rate of digital modulated signals. This approach is based on abrupt changes detection in time-frequency plane and on abrupt change periodicity analysis using Kalman filtering.

International audience; Recently, wireless technologies have known an increasing success, thus becoming an interesting field for study. One of the topics of research are multiple antenna arrays. Signal recovery in that case is not obvious. Different methods with different performances have been suggested. From a statistical analysis of errors at the output of zero-forcing, we have constructed a method, which we present in this article, that combines zero-forcing and maximum likelihood. We will demonstrate that it provides both a low complexity and nearly optimal results regarding binary error rate (BER). Furthermore, we will show its relevancy compared to the VBLAST algorithm.

International audience; This paper analyzes the suitability of various multiple access schemes for a 60 GHz mobile ad hoc network. The investigated techniques include multi-carrier modulation (OFDM-TDMA), the spectrum spreading method (DS-CDMA) and the combined schemes (MC-CDMA, MC-DS-CDMA) benefiting from the advantages of both techniques. The comparison between these different multiple access schemes is focussed on two aspects: (i) sensitivity to phase noise; the large available bandwidth around 60 GHz is very suitable for transmission of high data rate in indoor environments, but one issue in the 60 GHz band is the design of oscillators with moderate phase noise; (ii) robustness to imperfect power control; ad hoc networks consist of a set of mobile terminals communicating among themselves without any central controller; radio resource management has to be conducted in a distributed way and the power control is inherently imperfect.

Underwater object identification has been of great interest for a few years to acousticians (detection of boulders), marines (detection of buried mines), or archaeologists (detection of wreckage). Image and signal processing succeed in identifying objects lying on the sea bottom, however identification of an object buried in sediment remains complex. The purpose of this work is to develop a complete identification of objects embedded in the sediment using an adapted technology. We use a parametric source, whose properties are based on the nonlinear propagation characteristics of the water; it has many advantages as an acoustic source (high relative bandwidth, narrow beam) which are useful for object detection and classification. This paper presents two algorithms: the first one improves the object detection and the second procedure computes discriminant parameters from images to classify these objects.

Underwater object identification is of great interest to acousticians (detection of boulders), marines (detection of buried mines), or archaeologists (detection of wreckage). Image and signal processing succeed in identifying objects lying on the sea bottom, however identification of an object buried in sediment remains complex. The purpose of this work is to propose a complete identification of objects embedded in the sediment using an adapted technology. They use a parametric source, the properties of which are based on the water nonlinear propagation characteristics; it has many advantages as an acoustic source (high relative bandwidth, narrow beam) which are useful for object detection and classification. This paper presents a procedure which computes discriminant parameters from images to classify these objects.

Underwater object identification has been of great interest to acousticians (detection of boulders), marines (detection of buried mines), or archaeologists (detection of wreckage). Image and signal processing succeeds in identifying objects lying on the sea bottom, however identification of an object buried in sediment remains complex. The goal of this work is to obtain a complete identification and localization of objects embedded in sediment using adapted technology. The parametric source, whose properties are based on the nonlinear propagation characteristics of water, has many advantages as an acoustic source (high relative bandwidth, narrow beam) which are useful for object detection and classification.

International audience; The goal of the paper is to show that a Gaussian approximation can be used to model the global noise in a DS-CDMA system on a 60 GHz frequency band. We show that this approximation can also include the noise due to multipath and to imperfections in power control. The model can then be used as a first step and a reference when designing a communication architecture adapted to this frequency band for mobile indoor cellular systems.

International audience; With the rising number of modulation types used in multi-user communication systems, we need to find efficient methods to discriminate them. Indeed, modulation recognition has become important in wireless communications for both civilian and military applications. Traditionally, to classify modulation types, most studies assume abundant a priori knowledge about modulated signals such as binary data rate, baud rate or carrier frequency. However, new transmission/receiver systems need to classify automatically digital modulations without specific information. In the course of making decision on modulation type, these parameters may have to be estimated in order to perform efficient demodulation. We propose a new way of estimating the baud rate of digitally modulated signals and then some perspectives to estimate the binary data rate. This approach is based on abrupt changes detection in the time-frequency plane.