Performance of Dot-product preprocessing for Track-Before-Detect tracking of noise objects

• Autorzy: Mazurek P.
• Języki publikacji: EN

Abstrakty

EN

Track-Before-Detect (TBD) algorithms are applied for the tracking of signals below the noise floor. The noise object is the signal that has noise samples only. The processing of such signal using Spatio-Temporal TBD is not possible directly. The preprocessing technique based on the window approach and dot-product calculations emphasis the differences between global and local empirical distributions. The Monte Carlo tests are applied for the analysis of performance for two smoothing coefficients, different width of the window of analysis and different size of the object.

Słowa kluczowe

EN

tracking; estimation; track before detect; dot-product

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Computer Applications in Electrical Engineering
• Rocznik: 2013
• Tom: Vol. 11
• Strony: 447--454
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Mazurek P.

• West Pomeranian University of Technology, 71-126 Szczecin, ul. 26. Kwietnia 10

Bibliografia

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• [5] Mazurek P., Application of dot product for Track-Before-Detect tracking of noise objects, Poznan University of Technology Academic Journals - Electrical Engineering, no. 76, 101-107, 2013.
• [6] Mazurek P., Chi-square statistic for noise objects tracking in Track-Before-Detect systems, Poznan University of Technology Academic Journals - Electrical Engineering, no. 71, 177-184, 2012.
• [7] Mazurek P., Comparison of Different Measurement Spaces for Spatio-Temporal Recurrent Track-Before-Detect Algorithm, Advances in Intelligent and Soft Computing, vol. 102 - Image Processing and Communications Challenges 3, Springer Verlag, 157-164, 2011.
• [8] Mazurek P., Hierarchical Track-Before-Detect Algorithm for Tracking of Amplitude Modulated Signals, Advances in Intelligent and Soft Computing, vol. 102 - Image Processing and Communications Challenges 3, Springer Verlag, 511-518, 2011.
• [9] Mazurek P., Optimization of bayesian Track-Before-Detect algorithms for GPGPUs implementations, Electrical Review, R. 86 no. 7/2010, 187-189, 2010.
• [10] Mazurek P., Optimization of Track-Before-Detect systems for GPGPU, Measurement Automation and Monitoring, vol. 56 no. 7, 665-667, 2010.
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• [13] Stone L. D., Barlow C. A., Corwin T. L. Bayesian Multiple Target Tracking. Artech House, 1999.