De Los Santos, Paulo (2022) Estudio de procesadores GMTI para radares aerotransportados / Study of GMTI processors for airborne radars. Proyecto Integrador Ingeniería en Telecomunicaciones, Universidad Nacional de Cuyo, Instituto Balseiro.
![[img]](/style/images/fileicons/application_pdf.png)
| PDF (Tesis) Español 53Mb |
Resumen en español
En este proyecto integrador se estudian e implementan procesamientos orientados a detectar y localizar objetos en movimiento empleando un radar aerotransportado. A diferencia de un radar fijo, en un radar aerotransportado el espectro de frecuencias correspondiente a la señal indeseada o clutter se encuentra ensanchado y desplazado en frecuencia. Blancos que se encontrarían en la zona limpia del espectro si el radar no se moviese, ahora caen cerca o incluso dentro de la región de clutter, dificultando así su detección. Para este fin, se desarrolla una cadena de procesamiento GMTI, se estudian e implementan cada uno de sus eslabones y se verifican empleando datos reales. La cadena propone en su comienzo un acondicionamiento de la señal recibida, luego se realiza el algoritmo de compresión de pulso en tiempo rápido, se separan de pulsos, sigue el algoritmo FFT en tiempo lento, se compensan los efectos del ángulo de elevación, se realiza un filtrado MTI, se detectan blancos, se descompone el corrimiento Doppler, se posicionan las detecciones, se agrupan detecciones y finalmente, se realiza un seguimiento de blancos. Este ´ultimo procesamiento sólo fue verificado en datos simulados. Este trabajo se realiza en el marco del desarrollo del POD-ISR por parte de la empresa INVAP S.E.. Los datos reales adquiridos fueron captados por el primer modelo de evaluación tecnológica del POD-ISR y los datos simulados fueron generados por medio del simulador de datos radar SIDRA de la empresa INVAP S.E.. Además, toda la implementación está llevada a cabo en el lenguaje de programación python.
Resumen en inglés
This project studies and implements processing algorithm required to detect and locate moving objects using airborne radar. Unlike a fixed radar, in an airborne radar the frequency spectrum corresponding to the unwanted signal or clutter is broadened and shifted in frequency. Targets that would be in the clean area of the spectrum if the radar were not moving now fall close to or even within the clutter region, making them difficult to detect. To this end, a GMTI processing chain is developed, each of its links is studied and implemented, and verified using real data. The chain starts with the conditioning of the received signal, then the fast-time pulse compression algorithm is performed, the pulses are separated, the slow-time FFT algorithm follows, the effects of the elevation angle are compensated, MTI filtering is performed, targets are detected, the Doppler shift is decomposed, detections are positioned, detections are grouped, and finally, target tracking is performed. This last processing was only verified on simulated data. This work is carried out in the framework of the development of the POD-ISR by INVAP S.E. The real data acquired were captured by the first technological evaluation model of the POD-ISR and the simulated data were generated using the radar data simulator SIDRA of INVAP S.E. In addition, the whole implementation is carried out using the Python programming language.
| Tipo de objeto: | Tesis (Proyecto Integrador Ingeniería en Telecomunicaciones) |
|---|---|
| Palabras Clave: | Radar; [GMTI; DPCA; POD-ISR; Airborne; Aerotransportado] |
| Referencias: | [1] Richards, M. Fundamentals of Radar signal processing. 3a ed´on. Mc Graw Hill, 2022. 9, 13, 15, 38, 40, 41, 51, 52 [2] Dong, Z., Cai, B., Liang, D. Detection of ground moving targets for twochannel spaceborne sar-ati. EURASIP Journal on Advances in Signal Processing, 2010 (230785), 2010. 14 [3] Gierull, C. Statistical analysis of multilook sar interferograms for cfar detection of ground moving targets. Geoscience and Remote Sensing, IEEE Transactions on, 42, 691 – 701, 05 2004. 14 [4] Barton, D. Radar System Analysis and Modeling. Artech House, 2005. 15 [5] Nyquist, H. Certain topics in telegraph transmission theory. Transactions of the American Institute of Electrical Engineers, 47 (2), 617–644, 1928. 24 [6] Klemm, R. Principles of Space-Time Adaptive Processing. IET Radar, Sonar, Navigation and Avionics Series, 2006. 25 [7] Tam, W., Faubert, D. Improvement in the detection performance of a space based radar using a displaced phase center antenna. IEEE, Joint session JB13, 1987. 30 [8] Wang, X., Gao, G., Zhou, S., Zhu, Y. Performance comparison and assessment of displaced phase center antenna and along-track interferometry techniques used in synthetic aperture radar-ground moving target indication. Journal of Applied Remote Sensing, 8, 2014. [9] Deslauriers, C., Rousseau, L., Chouinard, J., Gierull, C. Comparison of gmti detectors for dual-channel scansar. Radar sensing and Exploitation Section, Defense Reaserch and Development Canada, 2017. 30 [10] Muhammad, B., Ahmed, H., Umar, A., B.A., C. Adaptive doppler compensation for mitigating range depende in forward-looking airborne radar. Electronics, 2020. 30 [11] Blum, R., Melvin, W., Wicks, M. An analysis od adaptive dpca. IEEE Transactions on Aerospace and Electronic Systems, 1996. 30 [12] Reed, L., Mallet, J., Brennan, L. Rapid convergence rate in adaptive arrays. IEEE Transactions on Aerospace and Electronic Sytems, AES-10, No. 6, 1974. 40 [13] Melvin, W., Scheer, J. (eds.) Principles of Modern Radar. Radar Applications, tomo 3. SciTech Publishing, 2014. 41, 51, 83 [14] Borsari, G. K., O., S. A. Cost-efficient training strategies for space-time adaptive processing algorithms. IEEE Proceedings of ASILOMAR - 29, 1996. 41 [15] Richards, M., Scheer, J., Holm, W. (eds.) Principles of Modern Radar. Basic Principles, tomo 1. SciTech Publishing, 2010. 45, 61, 63 [16] Schubert, E., Kriegel, H. P., Sander, J., Ester, M., Xu, X. Dbscan revisited, revisited: Why and how you should (still) use dbscan. ACM Transactions on Database Systems, 42 (3), 2017. 48 [17] Crouse, D. The tracker component library: Free routines for rapid prototyping. IEEE A and E Systems Magazine, 2017. 51 [18] Hyun, E., Lee, J.-H. A new os-cfar detector design. 2011 IEEE International Conference on Communications, Networking and Signal Processing (CNSI), 05 2011. 83 [19] Colena, C., Russell, M., Braun, S. Minesweeper: A novel and fast ordered-statistic cfar algorithm. 2020 IEEE High Performance Extreme Computing Conference (HPEC), págs. 1–6, 09 2020. 83 [20] Kay, S. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. 1a ed. Prentice Hall, 1993. 84 |
| Materias: | Ingeniería en telecomunicaciones > Análisis de sensado remoto |
| Divisiones: | INVAP |
| Código ID: | 1145 |
| Depositado Por: | Tamara Cárcamo |
| Depositado En: | 05 Jun 2023 15:56 |
| Última Modificación: | 05 Jun 2023 15:56 |
Personal del repositorio solamente: página de control del documento
