Abdelaziz Ouldali

Adaptive CA-CFAR threshold for non-coherent IR-UWB energy detector receivers

In the present letter, a new adaptive threshold comparison approach for time-of-arrival (TOA) estimation in ultra wideband (UWB) signals is proposed. This approach can be used with non-coherent energy detector receivers in UWB systems. It exploits the idea of cell averaging constant false alarm rate (CA-CFAR) used in radar systems, where the threshold changes every energy block. The performance of several approaches are compared via Monte Carlo simulations using the CM1 channel model of the standard IEEE 802.15.4a. Both simulation results and comparisons are provided highlighting the effectiveness of the proposed approach.

A new low complexity NLOS identification approach based on UWB energy detection

The major problem of indoor localization is the presence of Non-line-of-sight (NLOS) channels. In order to perform the NLOS identification, this paper proposes a new NLOS identification approach. It is based on the energy statistics of the direct-path pulse (DPP) and on the statistics of the delay between the strongest-energy pulse and the DPP energy of the received signal folded version. The simplicity of the proposed approach lies in the use of the parameters of the Energy-Based time of arrival (TOA) Estimation (EBE) algorithm. The CM1 and CM2 channel models of the standard IEEE802.15.4a are used. Numerical simulations results show that the correct identification of channel models with the proposed approach is better than with the multipath channel statistics based approach.

Joint Multiple Target Tracking and Classification Using Controlled Based Cheap JPDA-Multiple Model Particle Filter in Cluttered Environment

In this paper, we address the problem of jointly tracking and classifying several targets in cluttered environment. It is assumed that the motion model of a given target belongs to one of several classes. We propose to use the multiple model particle filter (MMPF) to perform nonlinear filtering with switching dynamic models. Moreover, the principle of joint probabilistic data association (JPDA) is used to determine the measurements origin. Besides, the joint probabilities are calculated using Fitzgeralds had hoc formulation (Cheap JPDA) whose efficiency has been proven in the literature. On the other hand, a controller based on the quality of the innovation has been implemented in order to tune the number of particles. The feasibility and the performances of the proposal have been demonstrated using a set of Monte Carlo simulations dealing with two maneuvering targets.

Evidential Data Association Filter

The problem of multi-target tracking in clutter environment has been shown to be very challenging for both the measurement to track association and the targets’ state estimation. Several approaches have been put forward to deal with such issue. Especially, the family of joint probabilistic data association and its modified versions has been very popular in the field. This paper advocates the use of the theory of belief function to tackle the measurement-to-track association as well as the estimation problems. The proposal generates the basic belief mass assignment using a Bayesian approach, while the decision making process is based on the extension of the frame of hypotheses. Our method has been tested for a nearly constant velocity target and compared to both the nearest neighbor filter and the joint probabilistic data associations filter in a highly ambiguous cases. The results demonstrate the feasibility of the proposal and show improved performances compared to the aforementioned alternative commonly used methods.

Joint TOA Estimation and NLOS Identification for UWB Localization Systems

In this paper, we propose a new joint time-of-arrival estimation and non-line-of-sight identification approach for ultra-wideband wireless sensor network applications. We use an energy-based time-of-arrival estimation algorithm. The non-line-of-sight detection is based on the direct path to the strongest multipath components ratio of the received signal folded version of the energy-based time-of-arrival estimation algorithm. The non-line-of-sight information is used in the weighted least-squares localization algorithm. The channel models residential LOS and residential NLOS of the standard IEEE802.15.4a are used. Numerical simulations results show that the correct identification of channel models with the proposed approach is better than those based on joint likelihood ratio and the location accuracy obtained by weighted least-squares algorithm using non-line-of-sight information is higher than that obtained by least-square algorithm.

Data Association in Multi-target Tracking Using Belief Function

In this paper, we present a new method for data association in multi-target tracking. The representation and the fusion of the information in our method are based on the use of belief function. The proposal generates the basic belief mass assignment using a modified Mahalanobis distance. While the decision making process is based on the extension of the frame of hypotheses. Our method has been tested for a nearly constant velocity target and compared with both the nearest neighbor filter and the joint probabilistic data associations filter in highly ambiguous cases. The results demonstrate the feasibility of the proposal and show improved performance compared to the aforementioned alternative commonly used methods.

Comparison of interactive multiple model particle filter and interactive multiple model unscented particle filter for tracking multiple manoeuvring targets in sensors array

Tracking multiple targets in cluttered environment has been acknowledged as a challenging task involving handling of measurement track-to-track uncertainty association in conjunction with nonlinearity and imprecision pervading the target dynamic models. In this paper an approach based on the use of an interacting multiple model particle filter (IMMPF) has been put forward, where the particle filter (PF) allows the system to handle non-linearity of the target cinematic models while the interacting multiple model (IMM) deals with the model switch when a target changes its manoeuvre. On the other hand, Cheap Joint Probabilistic Data Association (CJPDA) was used to tackle the data association problem. Two fusion architectures using the federated and the centralized form of Kalman filter were investigated. Performances and feasibility of the proposal are demonstrated through a set of Monte Carlo simulations involving three crossing targets. Also, a comparison analysis with an alternative approach using the IMM filter in conjunction with the Unscented Particle Filter (IMMUPF) is carried out. The results demonstrate the feasibility of the proposal and satisfactory tracking of the targets.

An evaluation of UWB localization under non line-of-sight (NLOS) propagation

In this paper we evaluate the statistical performances of the association of a low-complexity of the time of arrival (TOA) estimation algorithm and the location estimation algorithm in a non line-of-sight (NLOS) indoor environment. For that, we choose the time hopping (TH) code and pulse amplitude modulation (PAM) for ultra wideband (UWB) symbols and the IEEE802.15.3a models (CM1 and CM3) for the channel propagation. The numerical simulations show that the accuracy of TOA estimation can be achieved with only one training symbol period for data aided (DA) mode in LOS propagation (CM1). These performances are seriously degraded in NLOS propagation (CM3). Otherwise, the obtained results show the harmful effect of increasing the number of NLOS nodes (basic stations) on the positioning accuracy.

CA-CFAR threshold selection for IR-UWB TOA estimation

In this paper, we simplify the architecture of the cell averaging constant false alarm rate (CA-CFAR) approach used in time-of-arrival (TOA) estimation for impulse radio ultra wideband (IR-UWB) systems. The CA-CFAR approach uses the received signal samples provided by the non-coherent energy detection (ED) receivers. The modified approach is evaluated by Monte Carlo simulation on the CM1 channel model of the standard IEEE802.15.4a. The effects of the reference cells number and the guard cells duration on the performances of the modified CA-CFAR approach are studied. The simulation demonstrates that the modified approach gives better results than the conventional approaches.

Tracking objects in video sequence using active contour models and unscented Kalman filter

In this paper, we propose a new association of active contour model (ACM) with the unscented Kalman filter (UKF) to track deformable objects in a video sequence. The proposed approach is based on the use of the selective binary and Gaussian filtering regularization level set associated to the UKF (ACM-SBGFRLS-UKF) instead of the traditional level set (TLS) associated to the UKF (ACM-TLS-UKF). In fact, in the present work, we exploit the various advantages that the SBGFRLS offers compared to the TLS which suffers, from the sensibility to initials conditions and noise, to the impossibility to select partial or global segmentation and also from the complexity of the approach. Finally, a comparison study is presented, throughout several numerical simulations, of this new association approach ACM-SBGFRLS-UKF against the ACM-TLS-UKF for tracking deformable objects in a video sequence.