Theory of Adaptive Radar

Brennan, L. E.; Reed, L.S.

doi:10.1109/taes.1973.309792

Cited by 796 publications

(362 citation statements)

References 12 publications

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“…For convenience in the analysis to follow, the normalized steering vector in the space-time look-direction is defined to be Where η is some threshold. Using the densities in (8), the test in (9) becomes…”

Section: Signal Modelmentioning

confidence: 99%

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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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Section: Signal Modelmentioning

confidence: 99%

“…The test in (11) was the first STAP detection criterion, developed in the well-known papers by Brennan and Reed [8] and Reed, Mallet and Brennan (RMB) [3].…”

Section: |mentioning

confidence: 99%

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

Fathima¹,

Venu²

2017

IJET

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“…Ideally it provides coherent gain on target while forming doppler response nulls to suppress the disturbance components. Specifically the optimum doppler filter, which maximizes the output SINR [7], is given to within a scale factor by w = M −1 p , where M denotes the disturbance covariance matrix: the design of the optimum filter requires a-priori knowledge of the clutter covariance matrix. From a practical point of view, this knowledge is not available, and thus it is necessary to develop a processor which online estimates M and automatically adapts its filtering action in response to a changing environment.…”

Section: Problem Formulation and Design Issuesmentioning

confidence: 99%

Knowledge-based recursive least squares techniques for heterogeneous clutter suppression

Maio

Farina

Foglia³

2007

IET Radar Sonar Navig.

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In this paper we deal with the design of Knowledge-Based adaptive algorithms for the cancellation of heterogeneous clutter. To this end we revisit the application of the Recursive Least Squares (RLS) technique for the rejection of unwanted clutter and devise modified RLS filtering procedure accounting for the spatial variation of the clutter power. Then we introduce the concept of Knowledge-Based RLS and explain how the a-priori knowledge about the radar operating environment can be adopted for improving the system performance. Finally we assess the benefits resulting from the use Knowledge-Based processing both on simulated and on measured clutter data collected by the McMaster IPIX radar in November 1993.

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“…Hence, from the inverse matrix of the clutter correlation matrix R c and the desired wave's space-time steering vector s, the STAP weight is obtained [6,7] as where R c −1 is calculated by performing an eigen-expansion of R c and using its main eigenvalue λ j and eigenvector e j and the eigenvalue of the noise σ [1,7,8]:…”

Section: Pulse-doppler Radar and Stap Signal Processingmentioning

confidence: 99%

“…However, to make the beam width narrower and improve the angular resolution, an antenna with a large aperture would be necessary. To address these issues, in a radar equipped with an array antenna, space time adaptive processing (STAP) has been proposed as a two-dimensional clutter suppression filter to provide a resolution exceeding the Doppler frequency resolution and the beam width [6], and it is being actively investigated as a method of moving target detection for side-looking radars used for airborne early warning [7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Element‐localized Doppler STAP (Space Time Adaptive Processing) for clutter suppression in automotive forward‐looking RADAR

Ishihara

2006

Electron. Comm. Jpn. Pt. I

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SUMMARYIn forward-looking radars such as automotive radars, it is necessary to suppress the reflected undesirable signal (clutter) from such objects as the ground surface (especially hills), guard rails, and buildings, in order to detect moving targets ahead. When using a pulse-Doppler filter (PDF), which is the conventional method for clutter suppression, separation is difficult when the velocity of the target relative to the clutter is small. In this paper, as a high performance clutter suppression method for such low-velocity targets, we propose element-localized Doppler space time adaptive processing (ELD-STAP), which includes a PDF in the preprocessing, and which uses an array antenna. In the proposed ELD-STAP, only the PDF output corresponding to the Doppler frequency breadth of the clutter, predicted from the speed of the vehicle on which it is mounted, is selected for applying STAP, and hence the dimension of the data vector, which is the greatest difficulty in the application of STAP, can be reduced. By reducing the dimension of the data vector, not only the computation load, but also the number of cells that must be referenced to estimate the clutter correlation matrix (called secondary cells), can be reduced. Computer simulation reveals that the proposed ELD-STAP yields an improvement factor better than that provided by the combination of PDF and multibeam forming (MBF).

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Theory of Adaptive Radar

Cited by 796 publications

References 12 publications

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

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

Knowledge-based recursive least squares techniques for heterogeneous clutter suppression

Element‐localized Doppler STAP (Space Time Adaptive Processing) for clutter suppression in automotive forward‐looking RADAR

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