Theory of partially adaptive radar

Goldstein, J.S.; Reed, I. S.

doi:10.1109/7.625132

Cited by 162 publications

(92 citation statements)

References 21 publications

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“…This requirement is even more exacerbated when the MMSEbased receiver operates in a nonstationary environment. To alleviate computational complexity, the authors in [16][17][18][19][20] propose a considerably lower complexity version of the MMSE receiver that utilizes the reduced-rank multistage vector Wiener filter (MVWF). This MVWF technique obviates the necessity of either a covariance matrix inversion or an eigen-decomposition.…”

Section: Introductionmentioning

confidence: 99%

Multiuser Detection Using Adaptive Multistage Matrix Wiener Filtering Schemes with Stage-Selection Criteria in DS-UWB

Lin

2008

EURASIP J. Adv. Signal Process.

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Adaptive reduced-rank (RR) multistage matrix Wiener filtering (MMWF) techniques, based on the minimum mean-square error (MMSE) criterion, are proposed for direct-sequence (DS) ultra-wideband (UWB) communication systems. These RR-MMWFbased algorithms employ an adaptive fuzzy-inference determined filter stage. As a consequence, the proposed schemes achieve a substantial saving in complexity without compromising system performance and dynamic convergence/tracking capability. Additionally, the fuzzy-logic-controlled matrix conjugate gradient (MCG) algorithm is developed for a robust and reduced-rank implementation of the full-rank MMWF. Simulations are conducted to illustrate the convergence/tracking superiority and to provide a comparative evaluation of the proposed algorithms with the MMWF-based schemes using other adaptive stage-selecting criteria.

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Section: Introductionmentioning

confidence: 99%

Multiuser Detection Using Adaptive Multistage Matrix Wiener Filtering Schemes with Stage-Selection Criteria in DS-UWB

Lin

2008

EURASIP J. Adv. Signal Process.

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“…In cases where it is known that the interference is low rank (or approximately so) the amount of data required for adaptation can be reduced by using reduced rank estimation methods. Three proposed methods for making the selection of basis vectors are the Cross Spectral Metric (CSM) [1] method, the Principal Components Inverse (PCI) [2] method and Multistage Wiener Filter (MWF) [3]. The examination here is for detection of a signal that may or may not be present within a given set of data.…”

Section: Introductionmentioning

confidence: 99%

Case of Short Data Record for Both Training and Signal Detection

Freburger¹,

Tufts²

2000

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“…The data is then processed at one range of interest, which corresponds to a slice of the CPI data cube. This slice is a J ×K space-time snapshot whose individual elements correspond to the data from the jth pulse repetition interval (PRI) and the kth sensor element [2,6,7]. Hence this two-dimensional space-time data structure consists of element space information and PRI space-Doppler information.…”

Section: IImentioning

confidence: 99%

Comparative study on PC-SD and MWF Algorithms for STAP RADAR

Fathima¹,

Venu²

2017

IJET

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Abstract-The paramount challenge in the radar system is to alleviate the consequences of cold (homogeneous) clutter, severe dynamic (heterogeneous) hot clutter and jamming interferences while estimating the states of targets under track. To surmount this challenge, Space-Time Adaptive Processing (STAP) intensify the competence of radar systems. Space-time Adaptive Processing is a two-dimensional filtering technique for antenna array with multiple spatially distributed channels. The name 'Space-Time' elucidate the coupling of multifarious spatial channels with pulse-Doppler waveforms. The term "Adaptive processor" signifies that it can employ using a variety of algorithms on many platforms ranging from space satellites to a small low flying unmanned aerial. In order to develop STAP algorithms to operate in adverse environments, where intense environmental interference can reduce STAP proficiency to detect and track ground targets. STAP can effectively suppress these interferences and maximize the signal to interference plus noise ratio (SINR). Methods such as principal component analysis, Multi-stage Weiner Filter (MWF) are applied to STAP system. Rank and Minimum square error are parameters considered for estimating the performance of two stated techniques. Keywords-STAP (space Time Adaptive Processing), homogeneous clutter, heterogeneous clutter, PC-SD, MWF, Rank, MSE.I. INTRODUCTION An adaptive processing uses spatial and temporal domains for signal detection ,which offers significant advantages in a variety of applications including radar, sonar, and satellite communication [1].The signal processing for radar systems uses multiple antenna elements that coherently process multiple pulses. An adaptive array of spatially distributed sensors, which processes multiple temporal snapshots, surmount the directivity and resolution limitations. Specifically, STAP using STAP creates an aptness to suppress interfering signals while simultaneously conserving gain of the desired signal. Additional gain afforded by an array of sensors leads to enhancement in the signal-to-noise ratio, resulting in an ability to place deep nulls in the direction of interfering signals.Advanced airborne radar systems are equipped to detect targets in presence of both clutter and jamming. The ground clutter scrutinize by an airborne platform is extended in both angle and range and is spread in Doppler frequency because of the platform motion. STAP can significantly improve airborne radar performance. Computational complexity and the need to estimate non-stationary interference with limited data forces considerations of partially adaptive architectures. The STAP computational complexity is driven not just be the size of a single adaptive problem, but also by the number of adaptive problems that must be solved per coherent processing interval (CPI) [2].Fully adaptive STAP, though optimum given perfect knowledge, is impractical for two reasons. First is the computational burden of solving large system of equations in real-time. Second is the inte...

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Theory of partially adaptive radar

Cited by 162 publications

References 21 publications

Multiuser Detection Using Adaptive Multistage Matrix Wiener Filtering Schemes with Stage-Selection Criteria in DS-UWB

Multiuser Detection Using Adaptive Multistage Matrix Wiener Filtering Schemes with Stage-Selection Criteria in DS-UWB

Case of Short Data Record for Both Training and Signal Detection

Comparative study on PC-SD and MWF Algorithms for STAP RADAR

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