The main problem related to Persistent Scatterer (PS) interferometry is the lack of large point clouds in rural areas, although it has proven to be a powerful tool in urban scenarios, especially in monitoring buildings with possible slow temporal deformations. The identification of PSs in low Signal to Noise Ratio (SNR) areas is crucial and can be done using a multiple hypothesis test to detect the possible presence of multiple scatterers [1]. In this paper, we frame this problem by exploiting the Kullback-Leibler Information Criterion (KLIC), developed in [2], to address the design of one-stage adaptive sensing architectures for multiple hypothesis testing problems in PS interferometry. Theoretical analysis shows the equivalence between the algorithm developed in [1] and [2] for a single scatterer. In this context we use the scheme of multiple hypothesis, provided in [2], for both the formalization of rural PS detection problem and its solution.

In remote sensing, target detection in hyperspectral systems is a crucial duty since it enables the localization and discrimination of target features. For this purpose, reflectance spectra are frequently utilized, and the spectral signatures with corresponding component abundances in the observed scene are displayed. Nevertheless, many hyperspectral sensors have restricted spatial resolution, namely only a part of the pixel is occupied by the targets, and the spectra of multiple sub-pixel targets, along with the background spectrum, gets combined within a single pixel. Therefore, we propose in this paper a generalized replacement model that considers different sub-pixel target spectra and execute the detection process as a binary hypothesis test. This method shows to work well in handling this problem.

Next generation space-terrestrial-ocean integrated mobile networks providing global internet access that extend to the undersea are based on heterogeneous networks. In underwater applications, a key role is played by the acoustic positioning. In particular, this task can be accomplished making use of multiple passive sensors that estimate the differential signal delays employed for positioning. This paper exploits a methodology aimed at improving delay estimation by means of cross-cross-correlation, i.e., the cross-correlation between all the multi-sensor cross-correlations. The resulting equation system is formulated as a least squares (LS) minimization problem, whose solution is efficiently found resorting to the pseudo-inverse technique, ensuring a fast execution of the algorithm, without using statistical information on random signal spectra. The performance of the devised method is numerically analyzed for an extensive range of operating parameters to demonstrate the validity of the proposed approach in comparison with classic counterparts and theoretical optimum bounds.

One of the problems associated with electromagnetic imaging is that the interaction of photons with targets occurs only on part of their surface, namely those exposed to the transmitted energy rays. Imaging of deep localized objects is very hard especially in the presence of short electromgnetic wavelengths. In this paper we propose a new method for through wall imaging, based on photons and sound waves analysis. The technique investigates Doppler analysis in terms of estimating vibrations generated on infrastructures. The proposed method estimates target's vibration energy in order to perform tomographic imaging of man-made objects, such as buildings. Unlike traditional imaging, this technique allows for through wall imaging. The experimental results are distributed over one case study, where we show the to-mographic imaging of a reinforced concrete infrastructure. We consider this preliminary work very promising for future applications performed from the processing of satellite synthetic aperture radar images.

This paper tests a SAR image coregistration method, developed to account for a joint rotation and range/azimuth shift effect in absence of zooming, on foliage penetrating (FOPEN) data. In particular, the method is referred as a constrained Least Squares (CLS) optimization method and, in its basic form, it sharply extracts all patches composing the entire image. Differently, in next developments it applies a detection stage to identify extended areas in the images where patches are then selected. Moreover, it also performs a refinement of the equations in the CLS problem through an iterative cancellation procedure. The performance of this enhanced version of the CLS are made on the challenging Carabas-II VHF-band FOPEN SAR data to demonstrate its effectiveness also in high-resolution SAR images.

In this letter, a new approach for the retrieval of the vertical column concentrations of trace gases from hyperspectral satellite observations is proposed. The main idea is to perform a linear spectral unmixing by estimating the abundances of trace gases’ spectral signatures in each mixed pixel collected by an imaging spectrometer in the ultraviolet region. To this aim, the sparse nature of the measurements is brought to light and the compressive sensing paradigm is applied to estimate the concentrations of the gases’ endmembers given by ana prioriwide spectral library, including reference cross sections measured at different temperatures and pressures at the same time. The proposed approach has been experimentally assessed using both simulated and real hyperspectral datasets. Specifically, the experimental analysis relies on the retrieval of sulfur dioxide during volcanic emissions using data collected by the TROPOspheric Monitoring Instrument. To validate the procedure, we also compare the obtained results with the sulfur dioxide total column product based on the differential optical absorption spectroscopy technique and the retrieved concentrations estimated using the blind source separation.

This letter extends the constrained least-squares (CLS) optimization method developed to coregister multitemporal synthetic aperture radar (SAR) images affected by a joint rotation effect and range/azimuth shifts enforcing the absence of zooming effects. To take advantage of the structural information extracted from the scene, the method starts with a detection stage that identifies extended targets/areas in the images. The selected tie-points allow the CLS problem to be reformulated to find its (initial) solution based on a robust subset of image blocks. Then, the mean square error (MSE) of each equation evaluated from the initial solution allows to implement an iterative cancellation procedure to further skim the CLS equation set. The effectiveness of the proposed procedure is validated on real SAR data in comparison with the standard CLS.

This study aims at estimating the Earth deformations due to the nuclear test carried out by North Korea on the 3rdof September 2017 by processing a time series of synthetic aperture radar images acquired by the COSMO-SkyMed satellite constellation. For active satellite sensors working in the X-band, phase information can be unreliable if scenarios with dense vegetation are observed. This uncertainty makes difficult to correctly estimate both the interferometric fringes and the information phase delay generated by the variation in the space-time domain of the atmospheric parameters. To this end, in our research we apply the Sub-Pixel Offset Tracking technique, so that the displacement information is extrapolated during the coregistration process. The results reveal an accurate estimate of the spatial displacement of similar pixels due to the nuclear explosion. The work also reveals a hypothetical underground tunnel network.

This letter proposes a coregistration algorithm to compensate for the possible inaccuracy of trajectory sensor during the synthetic aperture radar (SAR) image acquisition process. Such a misalignment can be modeled as a pure displacement in range and azimuth directions and a rotation effect due to different angles of sight. The approach is formalized as a constrained least squares (CLS) optimization problem enforcing a constraint of the absence of a zooming effect between the two SAR images. Moreover, the system equations can optionally be weighted according to local properties between the extracted patches within the quoted couple. Interestingly, the solution can be obtained in closed form, therefore, with a low computational cost. The results of the tests conducted on the 9.6-GHz Gotcha SAR data demonstrate the capability of the strategy to properly register the imagery.

This letter considers the design of a two-stage direction of arrival (DOA) scheme for radar systems. Precisely, at the first stage a sparse recovery approach is used to obtain both DOA and complex amplitude estimates of the incoming signal. Since the DOA is evaluated on a predefined grid of bins sampling the antenna azimuth mainbeam, at the second stage, a closed-form complex-valued parabolic interpolation is performed to refine it. By doing so, the angle accuracy is improved, but at the same time maintaining fixed the overall computational complexity. Numerical results show the enhancement provided by the proposed procedure to the initial sparse recovery method.

Entropy concept is related to uncertainty and predictability of random time series. The estimated trend of such a parameter can provide useful information and possibly predict future behavior of a number of non-stationary noisy signals. The goal of this paper consists of analyzing the Covid19 signal made by the number of registered infections in Italy during the first four months of the pandemic epidemy (March-June 2020). Finally, some considerations are drawn after matching historical dates of some Covid-19 related Acts made by the Italian Government (i.e., lockdown and unlockdowns). Based on the obtained results, we could conjecture that the provisions have inducted people to a common behavior concerning local mobility during the lockdowns and the progressive unlockdowns of the quarantine period in Italy.

Magnetic resonance (MR) images can play a very important role to evaluate patients' diagnosis. In particular, there is an increasing interest in image processing and advanced texture analysis methods able to extract features from MR images that are not easily to percept by the human eye. Among many, Haralick's features have been strongly exploited referring to texture analysis of medical images. Therefore, in this paper, we have investigated Haralick's features computed from MR T2-weighted acquisitions in order to differentiate benign to malignant salivary gland tumors. The study has involved a total of 6 patients affected by salivary gland cancer: from the followup exams performed by radiologists, 3 patients have been identified as benign tumor affected while 3 patients as malignant one. Haralick's textural features are computed from normalized gray level co-occurrence matrix (GLCM) considering four different spatial relationships. In this preliminary study all the 14 Haralick's textural features are investigated in our attempt to differentiate benign from malignant salivary gland tumors: the obtained results reveal that these textural features may be useful to point out the differences between the tumor's nature, helping the clinicians with the diagnosis routine of the disease.

In this article, the problem of synthetic aperture radar (SAR) images coregistration is considered. In particular, a novel algorithm aimed at achieving a fine subpixel coregistration accuracy is developed. The procedure is based on the parabolic interpolation of the 2-D cross correlation computed between the two SAR images to be aligned. More precisely, from the 2-D cross correlation, a neighborhood of its peak value is extracted and the interpolation of both the 2-D paraboloid and the two alternative 1-D parabolas is computed to provide the finer misregistration estimation with subpixel accuracy. The main advantage of the proposed framework is that the overall computational burden is only due to the 2-D cross correlation estimation since the parabolic interpolation is calculated with a closed-form expression. The results obtained on real recorded unmanned aerial vehicle (UAV) SAR data highlight the effectiveness of the proposed approach as well as its capabilities to provide some benefits with respect to other available strategies.

Spectrum sensing (either cooperative or non-cooperative) is the key enabling technology to identify unused (free) frequency bands in dynamic spectrum access contexts. We propose a reputation-based cooperative spectrum sensing method that, improving the sensing performance of self-organizable networks, allows the detection and further rejection of all those malicious users that implement Byzantine attacks. The performances of our method are evaluated in terms of detection probability of the primary user, and in terms of the number of both correctly identified attackers and discarded honest users. The simulation results show the robustness of our method in detecting several kinds of Byzantine attacks, outperforming the (blind and non-blind) conventional approaches.

Cognitive radio is establishing itself as the most promising technology in tackling the problem of spectrum scarcity. It allows secondary users to opportunistically access and re-use the spectrum resources under-utilized by licensed or primary users. Spectrum sensing (either cooperative or non-cooperative modes) is exploited to identify those unused (free) frequency bands. This new technology has been proved to be vulnerable to an increasing number of attacks, such as Byzantine attacks. Here, we propose a novel reputation-based cooperative spectrum sensing method that first detects, and then rejects any malicious secondary user, thus improving the system performances. We evaluate the error probabilities (detection vs. false alarms) of the system, as well as the number of both correctly identified attackers and discarded honest users. Finally, we compare our method to a recently published reputation-based method (either blind or non-blind). As shown by the simulation results, the proposed method outperforms the conventional approach, confirming its robustness in detecting different types of Byzantine attacks.

In cognitive radio networks, automatic modulation recognition (AMR) is a fundamental step to perform the classification of different modulation formats. It plays an important role both in military and civil applications. For a cognitive radio receiver, AMR is the intermediate step between signal detection and demodulation. In this work, we propose a novel blind AMR algorithm to distinguish amongst both digital and analog signals. In particular, we exploit higher order moments as well as some features of the received signals, recognizing not only the modulation formats (amplitude, phase, and frequency) but also the levels of the constellations. We can classify up to 17 different (analog and digital) modulations. The simulation results confirm the validity of our approach for blind modulation recognition in cognitive radio applications.

We address adaptive radar detection of targets embedded in clutter characterized by a symmetrically structublack power spectral density (PSD) and persymmetric covariance matrix. At the design stage, such properties are jointly exploited to come up with decision schemes capable of guaranteeing superior detection performances with respect to architectures which incorporate either persymmetry or clutter PSD symmetry. The performance analysis, both on simulated and on real radar data, confirms the superiority of the newly proposed architectures over their natural counterparts which do not take advantage of both the sources of a priori information.

This paper presents an interdisciplinary application of communication services to business. In particular, an extrapolation algorithm for financial trading is here discussed by means of a preliminary case study. We exploit the hidden market trends of historical stock quotes applying signal processing to financial trading. Our case study consists of an example of binary options stock trading. Binary options trading is based on algorithms of financial data processing, that usually run on remote proprietary broker platforms, providing the customer with the proper option to possibly trade a given stock. Here, we have investigated the performance of a simple algorithm which includes one buy / sell order per week. We have analyzed real sets of historical stock quotes, evidencing the asymmetry of achievable economic returns. In fact, the devised signal processing algorithm has denoted a (simulated) overall trading gain in the 82% of cases, showing that engineering management fruitfully applies to financial stock trading.

This work investigates a new code acquisition technique for wireless communications in presence of cell correlation. Code synchronization must be addressed in the most rapid and efficient way: even a small misalignment can cause dramatic signal-to-noise ratio (SNR) degradation. Serial cell search is usually adopted for pseudo noise (PN) code acquisition to reduce the processing complexity in mobile terminals for spread spectrum (SS) communication systems. Unlike the simple case of one (timing) cell per chip, the detection variables between contiguous cells, for sizes less than one chip period, are not independent and possibly strongly correlated. We propose a new test that takes into account several correlated cells at once. Our numerical and simulation results show that our method drastically improves the conventional approach in terms of detection probability, allowing a significant reduction of the mean acquisition time in code synchronization for wireless communications. The performance improvement is obtained with a negligible increasing of the system computational complexity.

In cognitive radio networks, the unoccupied frequency bands licensed to primary users can be opportunistically accessed by secondary (low-power or hidden) cognitive users. Secondary users can be authorized low-power users, or unauthorized (hidden) users that occupy the band illegally transmitting under the noise level. More in details, the devised method is able to detect unknown low-power constant-modulus signals in noise of unknown variance, exploiting higher order moments of the received signal. The decision variable used in the detection stage is represented (only) by the estimated power of the hidden signal. Performance analysis is carried out in comparison with conventional energy detection, in the presence of noise uncertainty. In particular, the detection probabilities of the proposed and conventional methods as well as the mean detection time are evaluated and compared. The numerical results, obtained from wide simulation trials, have evidenced the efficiency of our method for detecting the hidden user's low-power signal in cognitive communications.

This paper addresses the problem of dynamic spectrum access, discussing a new method for spectrum sensing in cognitive radio networks. In particular, an innovative technique for the detection of an OFDM-based primary user signal is here proposed. Performance analysis is carried out in comparison with conventional spectrum sensing method that exploits the autocorrelation coefficients. Unlike the conventional method, our strategy is completely blind and can be applied with no a priori knowledge of any characteristics of the signals of interest. Simulation results have been carried out under operating settings, typical of wireless local area networks.

This work discusses a fast generation procedure of authentication codes, for multimedia content cryptography, whose length (and computational complexity) can be tuned accordingly to the specific mobile application and service. In this work, we propose a digital algorithm to generate a pair of long (asymmetric) keys from one short primitive key. According to our results, the devised procedure provides a watermarking algorithm to hide the authentication information inside the multimedia content (intra-frames of MPEG video streams or JPEG images) with the same robustness of similar previous attempts but with less computational complexity.

This work proposes an effective time-delay estimator for PN satellite signals, exploiting a fast triangular interpolator, running on three estimated ambiguity samples in the neighborhood of the coarse estimate. Performance analysis (theory and simulation) is carried out in comparison with conventional approaches based on the interpolation, usually carried out by (time-consuming) narrow-band over-sampling or (fast) fitting of few samples of a smoothed function of the ambiguity function around its maximum. The theoretical results, substantiated by computer simulations, have evidenced that the devised method outperforms the conventional estimator for all the timing offsets and is well suited for satellite spread-spectrum communications.

This paper addresses the problem of time-delay estimation and proposes an effective time-delay estimator for spread-spectrum communications. The main contribution of our work is twofold: first, we define a new objective function that analytically expresses the performance of different estimation criteria. Second, we introduce a new estimator that outperforms the conventional approaches. In particular, we develop a unified approach, deriving the performance trends of several time-delay estimators by one parametric closed form expression. Furthermore, we propose a new estimator that exploits a fast interpolation, running on few samples in the neighborhood of the coarse estimate, i.e. the (abscissa of the) estimated maximum of the ambiguity function. Mathematical expressions for bias and variance of the estimation error are derived and numerically evaluated by reduced Taylor's expansions up to the second order. The theoretical results, substantiated by computer simulations, have evidenced that the devised method is well suited for spread-spectrum satellite communications.

We present a novel video stream authentication scheme which combines signature amortization by means of hash chains and an advanced watermarking technique. We propose a new hash chain construction, the Duplex Hash Chain, which allows us to achieve bit-by-bit authentication that is robust to low bit error rates. This construction is well suited for wireless broadcast communications characterized by low packet losses such as in satellite networks. Moreover, neither hardware upgrades nor specific end-user equipment are needed to enjoy the authentication services. The computation overhead experienced on the receiver only sums to two hashes per block of pictures and one digital signature verification for the whole received stream. This overhead introduces a provably negligible decrease in video quality. A thorough analysis of the proposed solution is provided in conjunction with extensive simulations.

This contribution proposes an effective procedure for the acquisition of pseudo-noise code in satellite spread-spectrum localization systems. The main contribution of our work is twofold: first, we define a new objective function that is able to exploit the capabilities of different detectors in only one ambiguity function. Then, we introduce a compound detection procedure that, taking advantage of a fast interpolation of the optimum discrete samples, outperforms the conventional approaches. Wide simulation trials have been conducted to evidence that the devised methods are well suited for the incoming spread-spectrum satellite global localization systems.

This letter presents an efficient method for optical code division multiple access (OCDMA) code acquisition based on unipolar optical orthogonal codes. We propose a two-dwell acquisition procedure and provide closed form expressions to analyze the system's error probabilities. Our results match the Multiple Shift (MS) algorithm, recently introduced in the literature, and show that our procedure can achieve the same system performance with a lower computational complexity.

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.

In this work, we derive a blind equalizer that pursues the maximization of an objective function, consisting of the ratio between the square of the mean signal power and the variance of the signal power. The performance of the addressed equalizers is then investigated by focusing on DS/CDMA communication environments in a downlink scenario. In particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples, in terms of robustness against the effect of interference, as well as in terms of convergence rate, in spite of a small amount of extra processing.

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.

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.

This paper proposes a business model founded on Bayes decision test for video-call billing. This model is based on the end-to-end Quality of Service (QoS) obtained exploiting the tracing watermarking procedure recently introduced in literature. In particular, we employ the watermark embedded in each transmitted video-sequence to monitor the QoS of the communication link and then to adequately fare the user depending on the real received video-quality. We need to know only the MSE of the received watermark to estimate the end-to-end QoS of the communication link. Numerical results are conducted to characterize the effectiveness of the proposed method, using two different business scenarios, and confirm the validity of such approach. Therefore, the network operator is able to implement an adaptive billing strategy, depending on the effective received quality and maximizing the profit.

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 station's 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.

Satellite link presents peculiar characteristics like no packet reordering and low bit error rate. In this paper we leverage these characteristics combined with watermarking techniques to propose a novel authentication algorithm for multicast video streaming. This algorithm combines a single digital signature with a hash chain pre-computed on the transmitter side; the hash chain is embedded in the video stream by means of a watermarking technique. Our proposal shows several interesting features: authentication is enforced, as well as integrity of the received multicast stream; received blocks can be authenticated on the fly; no storage is required on the receiver side, except for the amount of memory needed to store a single hash; overhead computations required on the receiver sum up to single hash per block, while a digital signature verification is amortized over the whole received stream. Finally, note that the bandwidth overhead introduced is negligible, since the applied watermarking technique introduces virtually no modifications (at least, not recognizable by humans) on the original video stream pictures.

We consider the problem of source authentication of video streams in multicast environments. We proposed a novel algorithm which combines signature amortization based on hash chains and watermarking to embed hash chains in the video stream. The algorithm exploits a novel watermarking procedure using Reed-Solomon mark encoding which ensures error-free and fast convergence mark extraction. We show that the algorithm has a negligible impact on the video stream quality and we evaluate the configuration parameters of the algorithm which ensure proper verification of the source authenticity.

Tracing watermarking has been recently proposed as a technique to provide a blind measure of the quality of service of the communication link, focusing on multimedia communication scenarios. 3G communication scenarios, where each customer transmits both voice and MPEG-4 video sequences in real time, have been considered. Typical video-phone call consists of close shots of speakers, framing their face in the foreground. For such particular application, a novel colour space (YST) is adopted to minimise the perceptual distortions on face coding introduced by watermarking. In the YST space, the luminance component (Y) is the same as in conventional YUV space, whereas the vectors S and T lie within the chrominance (UV) plane. The S (skin) component is a linear combination of U and V obtained as the ‘average’ chrominance estimated from an assorted set human faces to achieve a reasonable generalisation. The third component, T, is defined as orthogonal to the YS plane. The results show the benefits obtained in digital watermarking by the new representation against the conventional approach. In fact, the sensitivity of the YST representation outperforms the conventional one in terms of objective (mean square error, peak signal-to-noise ratio) and subjective (video-quality metrics) indicators.

A new special function, called the modified generalized Q (MGQ) function, is here defined to analytically express the performance of the pseudonoise code acquisition based on matched filter correlators. In the considered case of two cells per chip, no convergent infinite series have been found in the open literature expressing the probabilities of false alarm and detection. The performance is analyzed in terms of mean acquisition time for signal-to-noise ratios of practical interest

Many studies have shown that color representation is very relevant in image processing and communications techniques. In this contribution, we propose a new color space, based on the "skin" component, in order to minimize the perceptual distortions introduced by digital watermarking. We have therefore defined a new color space, called YST, in which the brightness component is the same of YUV. Conversely, the S (skin) component has been obtained estimating the average values corresponding to a set of different colors of human faces. The criterion for this selection was to achieve a reasonable degree of generalization. The third component, T, is automatically identified by the Gram-Schmidt procedure in order to have an orthogonal color space. Analytical results are used to show the benefits obtained in digital watermarking by the new representation as well as in terms of peak signal-to-noise ratio and video quality metrics.

Noncoherent techniques can be adopted for pseudonoise code synchronization in the presence of random phase. Differentially coherent methods conversely operate with linear phase shifts, such as when a systematic frequency error occurs. This letter presents a method exploiting local phase coherence (inspired by the Pisarenko estimation), allowing global frequency estimation in the presence of random phase noise. Its accuracy is numerically compared with noncoherent and differential techniques for the initial stage of wideband code-division multiple-access code synchronization.

Testing for statistical distribution has received increasing attention in signal processing for communications. Noncoherent receivers, based on correlation magnitude, are employed when the actual carrier phase of the received samples is unknown. This paper presents a new test, based on high-order statistics, to decide whether a real positive white series is a realization of a Rayleigh-distributed random process. Such a "Rayleigh-ness" test is based on a testing variable that measures the "Ricianity" of the series under investigation. That is, it estimates the possible presence of the mean of the complex Gaussian model generating both Rayleigh and Rice distributions. The asymptotic testing statistics have been derived as explicit functions of the higher order moments of the noise-plus-interference distribution. The performance of the Rayleigh-ness test has been analyzed in comparison with a conventional power detector. The devised test has application to noncoherent initial synchronization of the chip offset (code acquisition) in a symbol-length spreading sequence of direct-sequence code-division multiple-access systems. In such a case, the noise-plus-interference variance under the out-of-sync condition is much larger than the effective variance in the in-sync case. The obtained results evidence the robustness of the Rayleighness test, avoiding the severe performance degradation in the presence of large Gaussian and non-Gaussian noise, as well as multiuser interference in a downlink scenario.

Multimedia data hiding by digital watermarking is usually employed for copyright protection purposes. In this contribution, a new application of watermarking is presented. Specifically, watermarking is here employed as a technique for testing the quality of service in multimedia mobile communications. A fragile known watermark is embedded in a MPEG-like host data video transport stream using a spread-spectrum technique to avoid visual interference. Like a tracing signal, a (known) tracing watermark tracks the (unknown) information stream that follows the same communication link. The detection of the tracing watermark allows dynamically evaluating the effective quality of the provided video services, depending on the whole physical layer (including the employed image co/decoder). The performed method is based on the mean-square-error between estimated and actual watermarks. The devised technique has been usefully applied to typical scenarios of mobile wireless multimedia communication systems, in presence of multipath channel and interfering users.

Third generation cellular systems (IMT2000/UMTS) are expected to provide a large number of innovative services with negotiated end-to-end quality of service (QoS). An object-based system for quality of service assessment is presented to evaluate blindly the quality of a multimedia communication link by means of an unconventional use of semi-fragile digital watermarking. Specifically, a known watermark is hidden into each single object of a MPEG-4 video using a spread spectrum technique. In this fashion, the object and the embedded watermark follow the same communication link. In fact, the degradations endured by the (known) watermark allows the degradations suffered, at the receiver's side, by the original (unknown) object to be inferred. The quality of service evaluation is based on the calculation of the mean square error between the estimated and the actual watermarks. Experiments show the effectiveness of the proposed method.

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.

The performance and the sensitivity of the neural correlator based on integral pulse frequency modulation (IPFM) are analyzed. The performance of the neural correlator is evaluated and shown to match many psychophysical test results. The behavior of the neural coder is expressed in terms of a stochastic nonlinear law. An analytical optimality condition for the mean-spike firing rate is derived. Numerical comparison between optimal and neurophysiological values shows that natural systems meet the optimality condition.>