• Journal of IKEEE
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• v.27 no.1
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• pp.38-44
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• 2023

Performance of a STAP(space-time adaptive processing) algorithm highly depends on how closely the estimated covariance matrix(CM) resembles the actual CM by the interference in CUT(cell under test). A STAP has 2 dimensional data structure determined by the number of array elements and the number of transmitting pulses and both numbers are generally not small. Thus, to meet the degree of freedom(DOF) of the CM, a huge amount of training data is required. This paper presents an algorithm to generate virtual training data from small received data, via converting them into the data in spatial frequency-Doppler plane. We theoretically derive where the clutter exist in the plane and present the procedure to implement the proposed algorithm. Finally, with the simulated scenario of small received data, we show the proposed algorithm can improve STAP performance.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.136-140
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• 2015

In this paper, a comparative studies on the STAP and SFAP were performed, which are known as representative anti-jamming technology for adaptive array antenna. As a method of estimating the weighting vector for simulation, MMSE(Minimum Mean Square Error) algorithm was commonly used and the analyses of the simulation performance in various jamming environments were presented. Especially, performance comparison between STAP and SFAP according to the jamming power J/S(Jamming to Signal Power Ratio), performance comparison in the ratio of jamming bandwidth to signal bandwidth, and performance comparison of BER between STAP and SFAP were presented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.730-736
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• 2013

Time-domain clutter generation model for airborne pulse doppler phase-array radar is presented. Time-domain surface clutter signal is generated assuming earth of a sphere and considering geometry of a clutter patch, and generation of sub-array clutter signal is presented. The generated sub-array clutter signal can be used by simulation input signal in various radar applications of DBF(Digital Beamforming), ABF(Adaptive Beamforming), Stap(Space-Time Adaptive Processing) and etc.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.37-44
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• 2014

The most effective method to overcome GPS jamming problem is to use an adaptive array antenna which has the capability of beamforming or nulling to a certain direction. In this paper, Space Time Adaptive Processing (STAP) beamforming algorithm of four elements array antenna will be designed and the anti-jamming performance will be analyzed. According to the analysis, the signal to noise ratio (SNR) and anti-jamming performance can be enhanced by beamforming algorithm. Also, the time tap effect of STAP algorithm will be analyzed theoretically and verified with array antenna modeling and simulation. Specially, the cautious selection of reference time tap in STAP can prevent the degradation of position accuracy performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.745-757
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• 2007

In this paper, we propose a design of GPS anti-jamming system and its operational method, which can effectively suppress interference and jamming signals induced in GPS receiver. The 7-array antenna used in the proposed system is composed of conventional 6 equi-spaced circular elements with one element on the center of antenna and can be efficiently operated under power-constrained conditions. Futhermore, in this paper, we analyze the structure and complexity of STAP and SFAP which are well known techniques in adaptive array antenna signal processing, and we compare the BER performances between STAP and SFAP in various jamming environment based on the same complexity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.20-27
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• 2010

In this paper, we presented a signal model of STAP and actual environment of clutter. The novel estimation method of clutter covariance matrix using median value is proposed to overcome serious performance degradation after NHD in nonhomogeneous clutter. Eigen value characteristic is improved through diagonal loading. Target detection ability and SINR loss of the proposed method though MSMI statistic is also compared with conventional method using average value. The simulation results, confirm the proposed method has better performance than others.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.4
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• pp.336-346
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• 2017

Applications of Sigma-Delta STAP, and a method of GMTI processing are presented for GMTI(Ground Moving Target Indication) mode of airborne radar with sigma, delta, and guard channels. We showed results of performance analyses of presented methods by clutter simulation with ICM(Internal Clutter Motion), signal processing simulation and MDV(Minimum Detectable Velocity). Presented methods for Sigma-Delta STAP and GMTI processing are easy to apply practically in GMTI mode of airborne radar without restriction by specific airborne radar system.

• Journal of IKEEE
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• v.26 no.4
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• pp.524-530
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• 2022

When radar return contains strong jammers along with ground clutter echo, a STAP(space-time adaptive processing) algorithms tend to suppress jammer components more severely than it does the clutter. This hinders moving target detection in that the target echo is apt to be buried by clutter echo. This paper presents a two-step STAP algorithm in which the pre-suppression of jammer by the spatial filtering is applied, prior to applying the STAP algorithm. We propose how to find the coefficients of the spatial filter and show that the spatial filtering barely alter the spectra of the target and the clutter echo, having only to suppress the jammers. Finally, we simulate a STAP scenario with strong jammers and show the proposed algorithm can improve STAP performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.661-669
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• 2017

This paper describes an MMTI(Maritime Moving Target Indicator) for periscope detection in airborne radar. Firstly, we analyze the characteristics of sea clutter, sea targets. Secondly, we study the differences between GMTI(Ground Moving Target Indicator) and MMTI. This paper proposes an optimal MMTI operating environment and method. We also suggest a signal processing algorithm using STAP(Space-Time Adaptive Processing) for detecting small RCS target moving low speed. The detection probability for moving target with MDV(Minimum Detectable Velocity) is simulated under various RCS and multi-channel system. Finally, we analyze the major performance for range, velocity and azimuth accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.72-79
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• 2009

This paper describes the performance evaluation of NHD(nonhomogeneity detector) for STAP(space-time adaptive processing) airborne radar according to various normalization methods in the nonhomogeneous clutter environment. In practice, the clutter can be characterized as random variation signals, because it sometimes includes signals with very large magnitude like impulsive signal due to the system environment. The received interference signals are composed of homogeneous and nonhomogeneous data. In this situation, NHB is needed to maintain the STAP performance. The normalization using the NHD result is an effective method for removing the nonhomogeneous data. The optimum normalization can be performed by a representative value considered with a characteristic of the given data, so we propose the K-means clustering algorithm. The characteristic of random variation data due to nonhomogeneous clutters can be considered by the number of clusters, and then the representative value for selecting the homogeneous data is determined in the clustering result. In order to reflect a characteristic of the nonstationary interference data, we also investigate the algorithm for a calculation of the proper number of clusters. Through our simulations, we verified that the K-means clustering algorithm has very superior normalization and target detection performances compared with the previous introduced normalization methods.