Comparison of topography- and aperture-dependent motion compensation algorithms for airborne SAR

This letter presents a comparison between threeFourier-based motion compensation (MoCo) algorithms forairborne synthetic aperture radar (SAR) systems. These algorithmscircumvent the limitations of conventional MoCo, namelythe assumption of a reference height and the beam-center approximation.All these approaches rely on the inherent time–frequencyrelation in SAR systems but exploit it differently, with the consequentdifferences in accuracy and computational burden. Aftera brief overview of the three approaches, the performance ofeach algorithm is analyzed with respect to azimuthal topographyaccommodation, angle accommodation, and maximum frequencyof track deviations with which the algorithm can cope. Also, ananalysis on the computational complexity is presented. Quantitativeresults are shown using real data acquired by the ExperimentalSAR system of the German Aerospace Center (DLR).

A Small Baseline DIFSAR Approach for Investigating Deformations on Full Resolution SAR Interferograms

This paper presents a differential synthetic apertureradar (SAR) interferometry (DIFSAR) approach for investigatingdeformation phenomena on full-resolution DIFSAR interferograms.In particular, our algorithm extends the capabilityof the small-baseline subset (SBAS) technique that relies onsmall-baseline DIFSAR interferograms only and is mainly focusedon investigating large-scale deformations with spatial resolutionsof about 100 100 m. The proposed technique is implemented byusing two different sets of data generated at low (multilook data)and full (single-look data) spatial resolution, respectively. Theformer is used to identify and estimate, via the conventional SBAStechnique, large spatial scale deformation patterns, topographicerrors in the available digital elevation model, and possibleatmospheric phase artifacts; the latter allows us to detect, onthe full-resolution residual phase components, structures highlycoherent over time (buildings, rocks, lava, structures, etc.), as wellas their height and displacements. In particular, the estimation ofthe temporal evolution of these local deformations is easily implementedby applying the singular value decomposition technique.The proposed algorithm has been tested with data acquired by theEuropean Remote Sensing satellites relative to the Campania area(Italy) and validated by using geodetic measurements.

Determination of sea surface salinity and wind speed by L-band microwave radiometry from a fixed platform

The European Space Agency Soil Moisture andOcean Salinity (SMOS) mission aims at obtaining global maps ofsoil moisture and sea surface salinity from space for large-scale andclimatic studies. It uses an L-band (1400–1427 MHz) MicrowaveInterferometric Radiometer by Aperture Synthesis to measurebrightness temperature of the earth’s surface at horizontal andvertical polarizations ( h and v). These two parameters will beused together to retrieve the geophysical parameters. The retrievalof salinity is a complex process that requires the knowledge ofother environmental information and an accurate processing ofthe radiometer measurements. Here, we present recent resultsobtained from several studies and field experiments that were partof the SMOS mission, and highlight the issues still to be solved.

Exact representation of antenna system diversity performance from input parameter description

A simplc formulation Io compute thc envelope correlation of anantenna divemiry system is dcrired. 11 is shown how to compute theenvelope correlation hom the S-parameter descnplian of the antennasystem. This approach has the advantage that i t does not require thecomputation nor the measurement of the radiation panem of theantenna system. It also offers the advantage of providing a clcaunderstanding ofthe effects ofmutual coupling and input match on thediversity performance of the antcnnii system.

Optimum Redundant Array Configurations for Earth Observation Aperture Synthesis Microwave Radiometers

Two-dimensional aperture synthesis radiometry is the technologyselected for ESA's SMOS mission to provide high resolution L-bandradiometric imagery. The array topology is a Y-shaped structure. Theposition and number of redundant elements to minimise instrumentdegradation in case of element failure(s) are studied.

BPSK to ASK signal conversion using injection-locked oscillators-Part I: theory

This paper presents a new method and circuit for the conversion of binary phase-shift keying (BPSK) signals into amplitude shift keying signals. The basic principles of the conversion method are the superharmonic injection and locking of oscillator circuits, and interference phenomena. The first one is used to synchronize the oscillators, while the second is used to generate an amplitude interference pattern that reproduces the original phase modulation. When combined with an envelope detector, the proposed converter circuit allows the coherent demodulation of BPSK signals without need of any explicit carrier recovery system. The time response of the converter circuit to phase changes of the input signal, as well as the conversion limits, are discussed in detail.

A leverage theory of reputation building with co-branding: Complementarity in reputation building

We present a leverage theory of reputation building with co-branding. We showthat under certain conditions, co-branding that links unknown firms in a new sectorwith established firms in a mature sector allows the unknown firms to signal a highproduct quality and establish their own reputation. We compare this situationwith a benchmark in which both sectors are new and firms signal their qualityonly with prices. We investigate how this comparison is affected by the nature ofthe technology linking the two sectors and a cross-sector inference problem thatconsumers might face in identifying the true cause of product failure. We find thatco-branding facilitates the process in which a Þrm in the new sector to signal itsproduct quality only if the co-branding sectors produce complementary inputs andconsumers face a cross-sector inference problem. We apply our insight to economicsof superstars, multinational firms and co-authorship.

Estimation of the parameters of the gravitational-wage signal of a coalescing binary system

The statistical theory of signal detection and the estimation of its parameters are reviewed and applied to the case of detection of the gravitational-wave signal from a coalescing binary by a laser interferometer. The correlation integral and the covariance matrix for all possible static configurations are investigated numerically. Approximate analytic formulas are derived for the case of narrow band sensitivity configuration of the detector.

Connections between signal processing and complex analysis

We describe one of the research lines of the Grup de Teoria de Funcions de la UAB UB, which deals with sampling and interpolation problems in signal analysis and their connections with complex function theory.

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

Alternative Techniques of Neural Signal Processing in Neuroengineering

Neural signal processing is a discipline within neuroengineering. This interdisciplinary approach combines principles from machine learning, signal processing theory, and computational neuroscience applied to problems in basic and clinical neuroscience. The ultimate goal of neuroengineering is a technological revolution, where machines would interact in real time with the brain. Machines and brains could interface, enabling normal function in cases of injury or disease, brain monitoring, and/or medical rehabilitation of brain disorders. Much current research in neuroengineering is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain–computer interfaces and neuroprosthetics.