Study Stap Algorithm on Interference Target Detect Under Nonhomogenous Environment

Gong, Qingyong; Zhu, Zhaoda

doi:10.2528/pier09101502

Cited by 13 publications

(13 citation statements)

References 22 publications

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“…Much of the research has been done on STAP with active radars using uniform linear array (ULA) [3,10,11] and circular array [4,5,7]. Some of the research exists on the clutter suppression of airborne radar [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Fpga Implementation of Space-Time Adaptive Processing (Stap) Algorithm for Target Detection in Passive Radars

Mahmood

Alam²,

Jamil³

et al. 2013

PIER C

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Abstract-Space-Time Adaptive Processing (STAP) algorithm has recently been used in Passive Bi-static Radars (PBR) because it removes the clutter and non-cooperative transmitter effectively making the target detection easy in harsh environments like air-ground. Realtime implementation of STAP is a very challenging task as it is computationally-intensive, time-critical and resource-hungry process. This paper focuses on the Field-Programmable Gate Array (FPGA) implementation of STAP algorithm for passive radar using FM radio as transmitter of opportunity. The signals of interest were collected using an eight-channel software-defined radar with a uniform circular array (UCA). The STAP processing was simulated using MATLAB and hardware implementation was carried out on a Xilinx Virtex-6 FPGA. The system is tested using experimental radar data. Timing and Power analysis of hardware implementation justifies that FPGA provides a fast and reliable platform for STAP real-time radar processing.

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Section: Introductionmentioning

confidence: 99%

Fpga Implementation of Space-Time Adaptive Processing (Stap) Algorithm for Target Detection in Passive Radars

Mahmood

Alam²,

Jamil³

et al. 2013

PIER C

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“…Many techniques were proposed and analyzed to suppress clutter in one or twodomain [1][2][3][4], which enhanced the out of signal-to-clutter-plus-noise ratio (SCNR) and improved the target detectability, discrimination and resolution. The methods in one domain contain adaptive polarization filter and moving target detection (MTI).…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Polarization-Space-Time Three-Domain Joint Processing for Clutter Suppression in Airborne Radar

Di-jun¹,

Xu²,

Zhang³

et al. 2012

PIER

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Abstract-An optimum polarization-space-time joint domain processing (PST-JDP) technique is proposed for clutter suppression which adequately adopts the three-domain information including the polarization, space and Doppler frequency information of the radar echo. The study shows that the polarization information together with the space and Doppler frequency information are effective to significantly enhance the clutter suppression performance for airborne radar. Several new techniques, (i.e., the covariance matrix eigendecomposition, the spectral analysis and the resolution grid method), are utilized for deriving the performance of the optimum PST-JDP. The main factors which affect on the performance of clutter rejection are the clutter degree of polarization, statistical distance of polarization between target and clutter, Doppler frequency of target and input clutter-to-noise ratio. The new optimum PST-JDP method outperforms significantly the traditional optimum space-time processing technology, especially in the case of the slowly or tangentially moving target. The simulation verifies the correctness and efficiency of the model.

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“…Preprocessing is an indispensable stage, because it can reduce false-alarm rate and increase detection rate through suppressing background clutter and enhancing target signature. So far, a lot of preprocessing algorithms have been brought up, some focus on space domain and some care about frequency domain [1][2][3][4][5], such as two-dimensional least mean square (TDLMS) filter [6], morphological filter [7], high-pass filter [8], median filter [9], nonlinear filter [10,11], local variance weighted information entropy (WIE) filter [12]. It is well known that performance evaluation is an essential part for an effective algorithm, so we focus on evaluating the performance of preprocessing algorithms for IR small target images.…”

Section: Introductionmentioning

confidence: 99%

Metrics for Performance Evaluation of Preprocessing Algorithms in Infrared Small Target Images

Diao¹,

Mao²,

Gui³

2011

PIER

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Abstract-Image preprocessing is commonly used in infrared (IR) small target detection to suppress background clutter and enhance target signature. To evaluate the performance of preprocessing algorithms, two performance metrics, namely PFTN (potential false targets number) decline ratio and BRI (background relative intensity) decline ratio are developed in this paper. The proposed metrics evaluate the performance of given preprocessing algorithm by comparing the qualities of input and output images. The new performance metrics are based on the theories of PFTN and BRI, which describe the quality of IR small target image, by representing the difficulty degree of target detection. Theoretical analysis and experimental results show that the proposed performance metrics can accurately reflect the effect of the image preprocessing stage on reducing false alarms and target shielding. Compared to the traditional metrics, such as signal-to-noise ratio gain and background suppression factor, the new ones are more intuitive and valid.

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Study Stap Algorithm on Interference Target Detect Under Nonhomogenous Environment

Cited by 13 publications

References 22 publications

Fpga Implementation of Space-Time Adaptive Processing (Stap) Algorithm for Target Detection in Passive Radars

Fpga Implementation of Space-Time Adaptive Processing (Stap) Algorithm for Target Detection in Passive Radars

Performance Analysis of Polarization-Space-Time Three-Domain Joint Processing for Clutter Suppression in Airborne Radar

Metrics for Performance Evaluation of Preprocessing Algorithms in Infrared Small Target Images

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