Gaetano Giunta

Blind quality assessment system for multimedia communications using tracing watermarking

This paper presents a novel method to blindly estimate the quality of a multimedia communication link by means of an unconventional use of digital fragile watermarking. Data hiding by digital watermarking is usually employed for multimedia copyright protection, authenticity verification, or similar purposes. However, watermarking is here adopted as a technique to provide a blind measure of the quality of service in multimedia communications. Specifically, a fragile watermark is hidden in an MPEG-like host data video transport stream using a spread-spectrum approach. Like a tracing signal, the watermark tracks the data, where it is embedded, since both the watermark and the host data follow the same communication link. The estimation of the tracing watermark allows dynamically evaluating the effective quality of the provided video services. This depends on the whole physical layer, including the employed video co/decoder. The performed method is based on the evaluation of the mean-square-error between the estimated and the actual watermarks. The proposed technique has been designed for application to wireless multimedia communication systems. According to the results obtained, the sensitivity of the detected tracing watermark on the quality of service (QoS) indices provides for some useful capabilities for analyzing future mobile Universal Mobile Telecommunications System (UMTS) services.

A Novel Approach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model

We propose a novel localization algorithm of mobile sensors based on wireless sensor networks providing RSSI measurements between the mobile and the fixed sensors (anchors) in the network. The algorithm selects and weights the RSSI measurements according to their strength, and it uses a propagation model to transform RSSI measurements into distances, in order to estimate the position of the mobile. The algorithm also uses a virtual calibration method of the propagation model that does not require human intervention. By an experimental setup we show that the localization algorithm increases the performance with respect to the commonly used least mean square algorithm showing also how to achieve a wished accuracy increasing the anchor density.

Dynamic LOS/NLOS Statistical Discrimination of Wireless Mobile Channels

This paper presents the problem of identifying whether a received signal at a base station is due to a line-of-sight (LOS) transmission or not (NLOS). This is a first step towards estimating the mobile stations location. We formulate the NLOS identification problem as a binary hypothesis test by exploiting the Rician factor estimation. In particular, results from wireless environments with simulated geometry showed that the new test can decide for a LOS or NLOS condition using a small amount of samples. Therefore, changes from NLOS to LOS propagation can also be tracked quickly. This information is of high significance for location purposes in a wireless cellular network since time-of-arrival (TOA) and time-difference-of-arrival (TDOA) information based on LOS connections can be weighted stronger in a location computing algorithm and hence can lead to higher positioning accuracy. Otherwise, if the connection is identified as NLOS it can be useful to adopt a 2-D signal processing (space-time processing) strategy with an antenna array, instead of using the high complexity of the TOA and TDOA methods.

Virtual Calibration for RSSI-Based Indoor Localization with IEEE 802.15.4

Localization systems based on Received Signal Strength Indicator (RSSI) exploit fingerprinting (based on extensive signal strength measurements) to calibrate the system parameters. This procedure is very expensive in terms of time as it relies on human operators. In this paper we propose a virtual calibration procedure which only exploits the measurements of the RSSI between pairs of anchors. In particular, we propose two procedures for virtual calibration and we evaluate their performance with respect to an ad-hoc calibration campaign by performing measures in an indoor environment with an IEEE 802.15.4 sensor network.

Reliability of signal processing technique for pavement damages detection and classification using ground penetrating radar

Ground penetrating radar (GPR) signal processing is a nondestructive technique, currently performed by many agencies involved in road management and particularly promising for soil characteristics interpretation. The focus of this paper is to assess the reliability of an optimal signal processing algorithm for pavement inspection. Preliminary detection and subsequent classification of pavement damages, based on an automatic GPR analysis, have been performed and experimentally validated. A threshold analysis of the error is carried out to detect possible damages and check if they can be predicted, while a second threshold analysis determines the nature of the damage. An optimum detection procedure is performed. It implements the classical Neyman-Pearson radar test. All the settings needed by the procedure have been estimated from training sets of experimental measures. The overall performance has been evaluated by looking at the usual receivers operating characteristic. The results show that a reasonable performance has been achieved by exploiting the spatial correlation properties of the received signal, obtained from an appropriate analysis of GPR images. The proposed system shows that automatic evaluation of subgrade soil characteristics by GPR-based signal analysis and processing can be considered reliable in a number of experimental cases.

Real-time video transmission in vehicular networks

This paper addresses the problem of real-time video transmission in vehicular networks. We show that the video quality of real-time services is greatly decreased when there is network congestion in different traffic situations. We propose a solution that applies frame skipping and transcoding together with frame rate reduction techniques over IEEE 802.11 based vehicular networks. Our approach improves the quality of video transmission while reducing the bandwidth consumption.

A self-synchronizing method for asynchronous code acquisition in band-limited spread spectrum communications

This paper addresses the problem of initial synchronization of pseudo-noise code. A new code acquisition technique for spread-spectrum communication systems using band-limited chip waveforms is presented. Unlike conventional power detector based on testing the estimated maximum of the ambiguity function, the devised detector exploits a fast parabolic interpolation, running on three estimated ambiguity samples in the neighborhood of the coarse estimate. Performance analysis is carried out in comparison with conventional detector. Mathematical expressions for the probability of false alarm and detection are derived. They are numerically evaluated, under operating settings, by a reduced Tayloriquests expansion up to the second order. The theoretical results, substantiated by computer simulations, have evidenced that the devised method is well suited for asynchronous spread-spectrum communications. In particular, the acquisition performance depends on the actual offset between the received and the reference code waveforms, which are randomly distributed (in chip-asynchronous systems) within one sampling period. In fact, the parabolic interpolation technique outperforms the conventional detector for a wide range of code offsets because it is able to self-synchronize the testing variable around the true offset.

Fine estimators of two-dimensional parameters and application to spatial shift estimation

This paper presents a fast technique for fine estimation of two-dimensional (2-D) parameters, based on a parabolic interpolation of the same ambiguity function samples, and aimed at block-oriented estimation of the spatial shift between pairs of images in video sequences. Expressions for the bias and variance of the position error and the prediction error are derived. The method is tested using a synthetically generated autocorrelation function, varying the directionality and the eccentricity factor, in order to compare the performance of the proposed 2-D estimator to the case of two separate one-dimensional (1-D) estimators. The method has also been applied in vision systems, evidencing encouraging results for estimating the parameters of sophisticated global motion models from real images.

Fast estimators of time delay and Doppler stretch based on discrete-time methods

Estimation of the time delay and the Doppler stretch of a signal is required in several signal processing applications, This paper is focused on the joint fine estimation of these two parameters by a fast interpolation of the estimated ambiguity function. Four discrete-time methods (viz. multirate, piecewise scaling, linear scaling, and indirect estimators), based on an orthogonal model, are introduced. Their mean square error is mathematically derived for random signals corrupted by additive random noises. The obtained expressions have been evaluated for some typical parameter sets in the reference case of Gaussian signals and noises. The numerical results, compared with the accuracy of a continuous-time estimator, show the near efficiency of the multirate estimator for a wide range of SNRs. In fact, the adjustable multirate estimator can operate under near optimal conditions, unlike the approximate (i.e., piecewise and linear) scaling and the indirect methods based on constant sampling rates.

Estimation of global motion parameters by complex linear regression

Global motion is very likely to occur in image sequences analysis. For example, it arises if the observer is moving during the sequence acquisition (ego-motion). Our aim is to get a simple method to estimate in a reliable may a set of parameters that can take into account the presence of a global motion component, using only local information. The novelty of our approach is in regarding spatial shift, change of scale, and rotation (corresponding to usual camera effects such as pan and zoom) as a two-dimensional (2-D) Doppler effect. The mathematical treatment is carried on in the complex plane, so that the results can be easily deduced as an extension of the one-dimensional (1-D) case; in this way, we obtain simple expressions, well suited for a practical realization of the estimate. The method has been experimentally validated by both real pictures with a synthetic motion and real image sequences.