Performance Degradation for the GLR Test-Statistics for Spatial Signal Detection
Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signalis is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.
[1] N.R.Goodman, ”Statistical analysis based on a certain multivariate Gaussian distribution”, Ann.Math.Stat., March, 1963, Vol.34.
[2] A. L. Swindlehurst and P. Stoica ”Maximum Likelihood Methods in Radar Array Signal Processing”. Proceedings of IEEE, vol.86,NO.2, February 1998.
[3] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, Prentice-Hall, 1998.
[4] H.L.Van Trees ”Detection, Estimation, and Modulation Theory” J.Wiley, New York, 1971.
[5] L.L.Scarf ”Statistucal Signal Processing”, Addison-Wesley, Reading, Mass., 1991.
[6] V.S. Pugatchev, ”The theory of probabilities and mathematical statistics”, Nauka, Moskwa, 1979, (in Russian).
[7] A.V. Klyuev, V.P. Samarin, V.F. Klyuev, Algorithm of Measurement of Noise Signal Power in the Presence of Narrowband Interference. ICECECE 2012: International Conference on Electrical, Computer, Electronics and Communication Engineering, 6-7 December 2012, Australia, Perth. Issue 72, pp. 15-18.
[8] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Estimation of efficiency of algorithm of measurement of power of noise on the background of narrowband interference. Information-measuring and Control Systems, vol. 10, no 6, pp.72-75, 2012.
[9] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Algorithm of measurement of power of noise on the background of irregular pulse interferences. Information-measuring and Control Systems, vol. 10, no 1, pp.76-79, 2012.
[10] Klyuev V.F. Samarin V.P. Klyuev A.V., Power measurement algorithm of input mixture components of the noise signal and narrowband interference. Vestnik of UNN, no 5(1), pp. 51- 55, 2012.
[11] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Nonlinear algorithms for measuring the noise signal power against the background of interferences. Radioelectronics and Communications Systems, vol. 56, no 6, pp. 304-311, 2013.
[12] Kwang June Sohn, Hongbin Li, Braham Himed: Parametric GLRT for Multichannel Adaptive Signal Detection. IEEE Transactions on Signal Processing 55(11), 2007.
[13] R. Klemm Principles of Space-Time Adaptive Processing. IEE Publishing, 2002.
[14] R. Klemm Applications of Space-Time Adaptive Processing, IEE Publishing, 2004.
[15] L. Brennan and I. Reed, Theory of adaptive radar, IEEE Transactions on Aerospace and Electronic Systems, vol. AES-9, no. 2, March 1973
[16] O.V. Bolkhovskaya, A.A. Maltsev, K.V. Rodushkin ”Comparative analysis of different statistics for spatial signal detecting in the short samples case”. Radiophysics and quantum electronics, Vol 47, N 8, 2004.
[17] O.V. Bolkhovskaya, A.A. Maltsev ”The performance of the GLRT for the spatial signals detection with a small number of observations”, IEEE Signal Processing Letters, Oct. 2004.
[18] Bolkhovskaya, O. V.; Mal’tsev, A. A. ”Determination of Threshold Values of the Generalized Likelihood Ratio in the Problem of Detecting Partially Coherent Spatial Signals in the Case of Short Samples”. Radiophysics and Quantum Electronics, Volume 45, Number 12 (2002) .
[19] O.V. Bolkhovskaya, A.A. Maltsev, ”Efficiency of different GLR teststatistics for spatial signal detecting”. ICECECE 2012: International Conference on Electrical, Computer, Electronics and Communication Engineering, 6-7 December 2012, Australia, Perth. Issue 72, pp. 260-265.
[20] Rodushkin K.V. , Ph.D. Thesis, 2001
[1] N.R.Goodman, ”Statistical analysis based on a certain multivariate Gaussian distribution”, Ann.Math.Stat., March, 1963, Vol.34.
[2] A. L. Swindlehurst and P. Stoica ”Maximum Likelihood Methods in Radar Array Signal Processing”. Proceedings of IEEE, vol.86,NO.2, February 1998.
[3] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, Prentice-Hall, 1998.
[4] H.L.Van Trees ”Detection, Estimation, and Modulation Theory” J.Wiley, New York, 1971.
[5] L.L.Scarf ”Statistucal Signal Processing”, Addison-Wesley, Reading, Mass., 1991.
[6] V.S. Pugatchev, ”The theory of probabilities and mathematical statistics”, Nauka, Moskwa, 1979, (in Russian).
[7] A.V. Klyuev, V.P. Samarin, V.F. Klyuev, Algorithm of Measurement of Noise Signal Power in the Presence of Narrowband Interference. ICECECE 2012: International Conference on Electrical, Computer, Electronics and Communication Engineering, 6-7 December 2012, Australia, Perth. Issue 72, pp. 15-18.
[8] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Estimation of efficiency of algorithm of measurement of power of noise on the background of narrowband interference. Information-measuring and Control Systems, vol. 10, no 6, pp.72-75, 2012.
[9] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Algorithm of measurement of power of noise on the background of irregular pulse interferences. Information-measuring and Control Systems, vol. 10, no 1, pp.76-79, 2012.
[10] Klyuev V.F. Samarin V.P. Klyuev A.V., Power measurement algorithm of input mixture components of the noise signal and narrowband interference. Vestnik of UNN, no 5(1), pp. 51- 55, 2012.
[11] V.F. Klyuev, V.P. Samarin, A.V. Klyuev, Nonlinear algorithms for measuring the noise signal power against the background of interferences. Radioelectronics and Communications Systems, vol. 56, no 6, pp. 304-311, 2013.
[12] Kwang June Sohn, Hongbin Li, Braham Himed: Parametric GLRT for Multichannel Adaptive Signal Detection. IEEE Transactions on Signal Processing 55(11), 2007.
[13] R. Klemm Principles of Space-Time Adaptive Processing. IEE Publishing, 2002.
[14] R. Klemm Applications of Space-Time Adaptive Processing, IEE Publishing, 2004.
[15] L. Brennan and I. Reed, Theory of adaptive radar, IEEE Transactions on Aerospace and Electronic Systems, vol. AES-9, no. 2, March 1973
[16] O.V. Bolkhovskaya, A.A. Maltsev, K.V. Rodushkin ”Comparative analysis of different statistics for spatial signal detecting in the short samples case”. Radiophysics and quantum electronics, Vol 47, N 8, 2004.
[17] O.V. Bolkhovskaya, A.A. Maltsev ”The performance of the GLRT for the spatial signals detection with a small number of observations”, IEEE Signal Processing Letters, Oct. 2004.
[18] Bolkhovskaya, O. V.; Mal’tsev, A. A. ”Determination of Threshold Values of the Generalized Likelihood Ratio in the Problem of Detecting Partially Coherent Spatial Signals in the Case of Short Samples”. Radiophysics and Quantum Electronics, Volume 45, Number 12 (2002) .
[19] O.V. Bolkhovskaya, A.A. Maltsev, ”Efficiency of different GLR teststatistics for spatial signal detecting”. ICECECE 2012: International Conference on Electrical, Computer, Electronics and Communication Engineering, 6-7 December 2012, Australia, Perth. Issue 72, pp. 260-265.
[20] Rodushkin K.V. , Ph.D. Thesis, 2001
@article{"International Journal of Electrical, Electronic and Communication Sciences:66369", author = "Olesya Bolkhovskaya and Alexander Maltsev", title = "Performance Degradation for the GLR Test-Statistics for Spatial Signal Detection", abstract = "Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signalis is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.
", keywords = "GLRT, Neumann-Pearson’s criterion, test-statistics, degradation, spatial processing, multielement antenna array", volume = "7", number = "11", pages = "1512-4", }
