Timing acquisition is critical to enabling the potential of ultra-wideband impulse radios in high-speed, short-range indoor wireless networking. To this end, optimum data-aided timing offset estimators are derived in this paper based on the maximum likelihood (ML) criterion. A generalized likelihood ratio test (GLRT) is employed to detect an ultra-wideband waveform propagating through dense mul...

Techniques have been proposed to estimate unknown antenna impedance due time-varying near-field loading conditions at multiple-input single-output (MISO) receivers. However, it remains unclear when a change occurs and estimation becomes necessary. In this letter, we address problem by formulating as hypothesis test. Our contributions include deriving generalized likelihood-ratio test (GLRT) det...

At present, there are many technical methods in the field of target detection, but detection greatly affected by direct-path signals and need support such as extracting pure signals, so they cannot be used under condition without-direct-path signals. In this paper, a distributed method is studied system. case achieved generalized likelihood ratio test (GLRT). same time, input echo time synchron...

Motivated by multichannel radar detection applications in the presence of both white Gaussian noise and Gaussian clutter with unknown power, we develop maximum likelihood parameter estimates for the disturbance process. Both cases with known and unknown white noise variance are treated. As the estimators do not admit closed-form solutions, numerical iterative procedures are developed that are g...

We consider the application of distributed space-time coding in wireless sensor networks (WSNs). In particular, sensors use a common noncoherent distributed space-time block code (DSTBC) to forward their local decisions to the fusion center (FC) which makes the final decision. We show that the performance of distributed space-time coding is negatively affected by erroneous sensor decisions caus...

This paper decribes a novel method for detecting nonstationary signals in colored noise. A first order complex autoregressive, or AR(l), signal model is used which restricts the application of the detector to low order signals, i.e., those which are well modeled by a low order AR process and have only a single spectral peak. The detector assumes the noise covariance is stationary and known. The...

In this article, we consider the problem of adaptive detection for a multichannel signal in the presence of spatially and temporally colored compound-Gaussian disturbance. By modeling the disturbance as a multichannel autoregressive (AR) process, we first derive a parametric generalized likelihood ratio test against compoundGaussian disturbance (CG-PGLRT) assuming that the true multichannel AR ...

In this paper, we consider local detection of a target in hyperspectral imaging and assume that the spectral signature interest is buried background which follows an elliptically contoured distribution with unknown parameters. order to infer parameters, two sets training samples are available: one set, taken from pixels close pixel under test, shares same mean covariance while second set farthe...

Multilook approaches have been applied in synthetic aperture radar (SAR) tomography (TomoSAR), for improving the density and regularity of persistent scatterers reconstructed from multipass SAR images both rural urban regions. operations assume that all a given neighborhood are similar height, thereby providing additional data recovering position reflectivity single scatterer, so higher signal-...

This paper presents the development and performance evaluation of a methodology for distinguishing between mainlobe and sidelobe detections that arise in adaptive radar systems operating in adverse environments. Various adaptive detection test statistics such as the adaptive matched filter (AMF), the generalized likelihood ratio test (GLRT) and adaptive coherence estimate (ACE), and combination...