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In this paper, we consider the problem of detecting a signal in Gaussian noise with unknown covariance matrix, in partially homogeneous environments where the test and training data samples share the same noise covariance matrix up to an unknown scaling factor. One solution to this problem is the adaptive subspace detector (ASD) with a single or multiple observations. However, the probabilities of false alarm and detection of this ASD have not been obtained yet. In this paper, these expressions are derived on the basis of a single observation, which are confirmed with Monte Carlo simulations. It is shown that the ASD has a constant false alarm rate property with respect to both the shared noise covariance matrix structure and the independent scaling of the noise in the test data. In addition, we prove that for the First-Order model where the signal of interest is assumed to be a deterministic but unknown vector, the ASD derived with the generalized likelihood ratio test is consistent with that derived with an ad hoc two-step design procedure. [ABSTRACT FROM AUTHOR]

Many algorithms for direction-of-arrival (DOA) estimation require the noise covariance matrix to be known or to possess a known structure. In many cases, the noise covariance is, in fact, estimated from separate measurements. This paper addresses the combined effects of finite sample sizes, both in the estimated noise covariance matrix and in the data with signals present. it is assumed that a batch of signal-free samples is available in addition to the signal-containing samples. No assumption is made on the structure of the noise covariance. In this paper, the asymptotic covariance of the weighted subspace fitting (WSF) algorithm is derived for the case in which the data are whitened using an estimated noise covariance. The expression obtained suggests an optimal weighting that improves performance compared to the standard choice. in addition, a new method based on covariance matching is proposed. Both methods are asymptotically statistically efficient. The Cramér-Rao lower bound (CRB) on the covariance of the estimate for the data model is also derived. Monte Carlo simulations show promising small sample performance for the two new methods and confirm the asymptotic results. [ABSTRACT FROM AUTHOR]

We investigate the problem of enumerating source signals impinging on an array of sensors given noisy, limited observations. The assumption of a large sample size is indispensable for most of the existing approaches so that they suffer significant performance degradation when only a small number of samples is available. Random matrix theory can capture the asymptotic distributions of the eigenvalues accurately and provide good approximations even for a finite sample size. In this paper, we take into account the relationship and distributions of the noise and signal eigenvalues based on random matrix theory and derive a simple two-step test. Numerical simulations demonstrate that it is capable of correctly determining the number of sources in the case of small sample sizes. [ABSTRACT FROM PUBLISHER]

This paper presents the results of a comprehensive study of the shingled writing process and various signal processing and data detection approaches applied to the readback waveforms. The recording simulations include realistic head fields, a random granular media, magnetostatic and exchange interactions, and a READ head sensitivity function. Readback waveforms are examined in both one and two dimensions in terms of signal characteristics (linear and nonlinear), noise behavior (stationary and signal-dependent), and intertrack interference. Different equalization and detection approaches are compared and about a 10% density gain is reported for such 2-D magnetic recording compared with traditional single-track recording. These gains depend strongly on the number of readers, the reader positioning, and the reader width. [ABSTRACT FROM AUTHOR]

The problem of accuracy evaluation is one of the most time consuming tasks during the fixed-point refinement process. Analytical techniques based on perturbation theory have been proposed in order to overcome the need for long fixed-point simulation. However, these techniques are not applicable in the presence of certain operations classified as un-smooth operations. In such circumstances, fixed-point simulation should be used. In this paper, an algorithm detailing the hybrid technique which makes use of an analytical accuracy evaluation technique used to accelerate fixed-point simulation is presented. This technique is applicable to signal processing systems with both feed-forward and feedback interconnect topology between its operations. The acceleration obtained as a result of applications of the proposed technique is consistent with fixed-point simulation, while reducing the time taken for fixed-point simulation by several orders of magnitude. [ABSTRACT FROM PUBLISHER]

In this paper, we present a theoretical convergence analysis of the affine projection algorithm (APA) based on the arguments of energy conservation. Although the APA and its convergence analysis have been widely studied, the dependency of weight-error vector on past noise is usually neglected for simplicity. To obtain accurate theoretical results for the APA, we here consider the dependency between the weight-error vector and past noise in the mean-square analysis presented by Shin and Sayed in [“Mean-square performance of a family of affine projection algorithms,” IEEE Transactions on Signal Processing, vol. 52, no. 1, pp. 90–102, January 2004]. Through this work, we can also theoretically analyze the behavior of the periodic APA, which updates its weights periodically. Simulation results show that our theoretical results coincide closely with simulations. [ABSTRACT FROM AUTHOR]

In this paper, the second-order extended (SOE) H\infty filter for nonlinear discrete-time systems is derived based on an approximation to the quadratic error matrix. The solution is obtained by the game theory approach. It is shown that the result bears a strong resemblance to the SOE Kalman filter when the performance bound goes to infinity. An example of vehicle state tracking is simulated to compare the performances of the SOE Kalman filter, the first order extended and the SOE H\infty filter. Noises with unknown bias are injected into both process dynamics and measurements. The results show that the SOE H\infty filter has the smallest state tracking error. [ABSTRACT FROM AUTHOR]

In this paper, the stability boundaries of higher order 1-bit bandpass (BP) \Sigma-\Delta modulators for single- and dual-sinusoidal inputs are determined using quasi-linear modeling together with the describing-function method. Closed-form mathematical expressions are derived for the stability curves for different quantizer gain values. The stability prediction for the maximum stable input limits for eighth- and tenth-order (i.e., effective fourth- and fifth-order) inverse-Chebyshev- and Butterworth-based BP \Sigma-\Delta modulators for different stopband attenuation and bandwidths are established. The theoretical results are shown to be in good agreement with the simulation results for a variety of input amplitudes, bandwidths, and modulator orders. The proposed mathematical models of the quantizer will immensely help speed up the design of higher order BP \Sigma-\Delta modulators. [ABSTRACT FROM AUTHOR]

This paper examines the electromagnetic interference (EMI) due to the existence of U-shape I/O ports used for connection with RJ-45 connectors. These ports result in noise when image planes are used. The investigation also provides a useful approach to potentially reduce this noise source. U-shape I/O ports are a popular printed circuit board (PCB) structure and exist on PCBs used for information technology equipment, where image planes are generally referred to conducting layers in the vicinity of the electric circuits and signal sources such as a power plane, ground plane, and chassis plane. Both numerical simulations and measurements are employed in the examination, and they exhibit useful characteristics to detect and reduce the influence of EMI on PCBs. [ABSTRACT FROM PUBLISHER]

Multibaseline phase unwrapping is a critical processing procedure of multibaseline synthetic aperture radar interferometry (InSAR). It has an advantage over single-baseline phase unwrapping in discontinuous-terrain-height estimation. In this paper, the pixels' combination information of multiple InSAR interferograms with different baseline lengths is deeply investigated, and the term ambiguity vector is proposed to represent a pixel's ambiguity number of multiple interferograms. It is also revealed that pixels with the same ambiguity vector have an exclusive pattern among them. A fast cluster-analysis (CA)-based method is proposed for multibaseline phase unwrapping. In this method, all pixels are first clustered into different groups according to their patterns, and then, information of the cluster center is used to unwrap the phases of pixels group by group. Simulation results are shown to verify the effectiveness, efficiency, and noise robustness of CA multibaseline phase-unwrapping method. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the nonasymptotic behavior of the inn likelihood method in the context of lacunar array processing. We derive an analytical expression of the maximum. likelihood mean square error, which is now valid for all signal-to-noise ratio (SNR) ranges. We also provide an analysis of the SNR threshold phenomena, which allows us to derive closed-form formulas for the threshold values. Computer simulations confirm the validity of the theoretical investigations. [ABSTRACT FROM AUTHOR]

This paper describes a new type of regular structured low-density parity-check (LDPC) code: the partition-and-shift LDPC (PS-LDPC) code. PS-LDPC codes can be easily designed to have Large girth. The code construction is simple to explain: we divide the bit and check nodes in the Thnner graph into subsets and connect nodes in these subsets according to a set of parameters called shifts. We derive a general theorem on the shifts to prevent cycles that are harmful to LDPC decoding. This theorem provides a methodology to design PS-LDPC codes with arbitrary column weight j and large girth g. Simulation results over EPR4 channels demonstrate the good bit-error rate performance of PSLDPC codes. [ABSTRACT FROM AUTHOR]

A novel number theoretic transform called Inverse Gray Robust Symmetrical Number System (IGRSNS) is proposed for error control coding in this paper. IGRSNS is obtained by modifying Robust Symmetrical Number System (RSNS) that was proposed earlier, using Inverse Gray code property. Due to ambiguities present in each residue, RSNS has a short dynamic range (DR) compared to that in other number systems. The short DR of RSNS enables it to be effectively used for error detection without the addition of any redundant modulus as in Redundant Residue Number System. Although RSNS has a large redundant range, its detection ability is not optimal due to the Gray code property associated with it. In an attempt to overcome this limitation, we have proposed Inverse Gray coding to be combined with RSNS in increasing its effectiveness in error detection. The resulting IGRSNS thus inherits properties of both RSNS and Gray code. Analysis and simulations show that IGRSNS has a near-optimal error detection ability. The potential of IGRSNS for error correction is also investigated. Further, a novel error correction algorithm using one redundant modulus is proposed. Simulations show that the proposed algorithm performs well under all cases of single bit errors. [ABSTRACT FROM PUBLISHER]