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- research-articleJanuary 2024
Multikernel adaptive filtering over graphs based on normalized LMS algorithm
AbstractTo address the difficulty and inflexibility associated with choosing kernel parameters for single kernel adaptive filters (KAFs), this article proposes a multikernel adaptive filter for graph signals based on the least mean square (LMS) ...
Highlights- Multikernel adaptive filters based on LMS strategy for graph signals are proposed.
- Proposed graph filters combine multiple Gaussian kernels with different parameters.
- A coherence-check method is employed to reduce the computational ...
- research-articleSeptember 2023
Partial-update strictly linear, semi-widely linear, and widely linear geometric-algebra adaptive filters
Highlights- Widely linear, semi-widely linear and strictly linear AFs are constructed in the GA domain. As different from the GA-LMS, the GA-LMS algorithm proposed in ...
Geometric-algebra based adaptive filters have been successfully employed in many applications such as computer vision, data fusion and linear prediction where the unknown parameters of interest are high-dimensional multivectors. ...
- research-articleJuly 2019
Robust adaptive filtering algorithm based on maximum correntropy criteria for censored regression
Signal Processing (SIGN), Volume 160, Issue CPages 88–98https://doi.org/10.1016/j.sigpro.2019.01.026Highlights- This paper provides the development of the robust censored adaptive algorithm for the impulsive noise.
Censored observations and impulsive measurement noise are encountered in many practical applications of adaptive signal processing. Traditional adaptive filtering algorithms may fail to work in such cases. This paper proposes a robust ...
- research-articleApril 2017
Distributed pseudolinear estimation and UAV path optimization for 3D AOA target tracking
Signal Processing (SIGN), Volume 133, Issue CPages 64–78https://doi.org/10.1016/j.sigpro.2016.10.012We address the problem of angle-of-arrival (AOA) target tracking using multiple unmanned aerial vehicles (UAVs) in three-dimensional (3D) space. A distributed 3D AOA target tracking method is proposed consisting of a distributed estimator and path ...
- research-articleJanuary 2017
Multistatic pseudolinear target motion analysis using hybrid measurements
Signal Processing (SIGN), Volume 130, Issue CPages 22–36https://doi.org/10.1016/j.sigpro.2016.06.004This paper presents a new hybrid pseudolinear estimator (PLE) for target motion analysis of a constant-velocity target in the two-dimensional plane using angle-of-arrival, time-difference-of-arrival and frequency-difference-of-arrival measurements ...
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- research-articleJanuary 2017
On the asymptotic bias of the diffusion-based distributed pareto optimization
Signal Processing (SIGN), Volume 130, Issue CPages 337–342https://doi.org/10.1016/j.sigpro.2016.05.023We revisit the asymptotic bias analysis of the distributed Pareto optimization algorithm developed based on the diffusion strategies. We propose an alternative way to analyze the asymptotic bias of this algorithm at small step-sizes and show that the ...
- research-articleAugust 2016
Single-platform passive emitter localization with bearing and Doppler-shift measurements using pseudolinear estimation techniques
Signal Processing (SIGN), Volume 125, Issue CPages 336–348https://doi.org/10.1016/j.sigpro.2016.01.023The maximum-likelihood (ML) estimator for single-platform Doppler-bearing emitter localization does not admit a closed-form solution and must be implemented using computationally demanding iterative numerical search algorithms. The iterative ML solution ...
- research-articleDecember 2015
Analysis of a reduced-communication diffusion LMS algorithm
Signal Processing (SIGN), Volume 117, Issue CPages 355–361https://doi.org/10.1016/j.sigpro.2015.06.006In diffusion-based algorithms for adaptive distributed estimation, each node of an adaptive network estimates a target parameter vector by creating an intermediate estimate and then combining the intermediate estimates available within its closed ...
- research-articleDecember 2015
On the mean-square performance of the constrained LMS algorithm
Signal Processing (SIGN), Volume 117, Issue CPages 192–197https://doi.org/10.1016/j.sigpro.2015.05.011The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality-constrained adaptive filtering algorithms. Its main advantages are adaptability and relative simplicity. In order to gain analytical insights into the ...
- research-articleJune 2015
Adaptive waveform and Cartesian estimate selection for multistatic target tracking
Signal Processing (SIGN), Volume 111, Issue CPages 13–25https://doi.org/10.1016/j.sigpro.2014.11.022This paper considers the problem of target tracking by a multistatic radar system. In order to use linear Kalman filtering for tracking, the time delay, Doppler shift and arrival angle measurements from multiple receivers are transformed into target ...
- research-articleApril 2015
Adaptive frequency estimation of three-phase power systems
Signal Processing (SIGN), Volume 109, Issue CPages 290–300https://doi.org/10.1016/j.sigpro.2014.11.018The frequency of a three-phase power system can be estimated by identifying the parameter of a second-order autoregressive (AR2) linear predictive model for the complex-valued αβ signal of the system. Since, in practice, both input and output of the AR2 ...
- articleApril 2013
Modified quasi-OBE algorithm with improved numerical properties
Signal Processing (SIGN), Volume 93, Issue 4Pages 797–803https://doi.org/10.1016/j.sigpro.2012.09.024The quasi-OBE (QOBE) algorithm is a set-membership adaptive filtering algorithm based on the principles of optimal bounding ellipsoid (OBE) processing. This algorithm can provide enhanced convergence and tracking performance as well as reduced average ...
- articleJanuary 2013
Steady-state mean squared error and tracking performance analysis of the quasi-OBE algorithm
Signal Processing (SIGN), Volume 93, Issue 1Pages 100–108https://doi.org/10.1016/j.sigpro.2012.07.005The quasi-OBE (QOBE) algorithm is a set-membership adaptive filtering algorithm based on the principles of optimal bounding ellipsoid (OBE) processing. This algorithm can provide enhanced convergence and tracking performance as well as reduced average ...
- articleSeptember 2012
Affine projection algorithm with selective projections
Signal Processing (SIGN), Volume 92, Issue 9Pages 2253–2263https://doi.org/10.1016/j.sigpro.2012.02.018In the affine projection adaptive filtering algorithm, convergence is sped up by increasing the projection order but with an unwelcome consequence of increased steady-state misalignment. To address this unfavorable compromise, we propose a new affine ...
- articleJune 2012
Low-complexity adaptive decision-feedback equalization of MIMO channels
Signal Processing (SIGN), Volume 92, Issue 6Pages 1515–1524https://doi.org/10.1016/j.sigpro.2011.12.012A new adaptive MIMO channel equalizer is proposed based on adaptive generalized decision-feedback equalization and ordered-successive interference cancellation. The proposed equalizer comprises equal-length subequalizers, enabling any adaptive filtering ...
- articleJuly 2008
Exploiting geometry for improved hybrid AOA/TDOA-based localization
Signal Processing (SIGN), Volume 88, Issue 7Pages 1775–1791https://doi.org/10.1016/j.sigpro.2008.01.015In this paper we examine the geometrically constrained optimization approach to localization with hybrid bearing (angle of arrival, AOA) and time difference of arrival (TDOA) sensors. In particular, we formulate a constraint on the measurement errors ...
- articleMay 2008
Optimal angular sensor separation for AOA localization
Signal Processing (SIGN), Volume 88, Issue 5Pages 1248–1260https://doi.org/10.1016/j.sigpro.2007.11.013This paper establishes the angular separation requirements for angle-of-arrival (AOA) sensors in order to achieve the best mean squared error (MSE) localization performance for arbitrary but fixed sensor ranges. Optimal sensor placement for localization ...
- articleMarch 2004
On the bias of linear least squares algorithms for passive target localization
Signal Processing (SIGN), Volume 84, Issue 3Pages 475–486https://doi.org/10.1016/j.sigpro.2003.12.002The paper derives analytical bias expressions for the least squares bearings-only target localization algorithms. A detailed analysis of the interplay between the target localization geometry and the estimation bias is provided for the cases of ...
- articleMarch 2004
Passive emitter localization using weighted instrumental variables
Signal Processing (SIGN), Volume 84, Issue 3Pages 487–497https://doi.org/10.1016/j.sigpro.2003.11.014The linear least-squares algorithms for emitter localization such as the pseudolinear estimator are known to exhibit large estimation bias because of the correlation between the measurement matrix and the bearing noise. The paper presents a new bearings-...