Abstract
This paper analyzes the acoustic and micro seism signal feature of the projectile launching, flight and landing explosion in range test, and puts forward a Landing Point Location method which based on the asynchronous time difference of arrival (ATDOA) method. This method can effectively filter away the signals in launching and flight process, meanwhile get the acoustic and micro seism signal of projectile explosion accurately, and then the explosion location and velocity can be obtained by iterative equations. Comparing with the existing projectile point positioning method, this method can find the arrival time of explosion signal accurately, and establish the composition equations by iterative calculation equation of the respective location without precise synchronization of each sensor. Accordingly, the complexity of the application system is reduced, and positioning precision is improved effectively.
Similar content being viewed by others
References
Allen RV (1978) Automatic earthquake recognition and timing from single traces. Bull Seismol Soc Am 68(5):1521–1532
Canclini A, Bestagini P, Antonacci F et al (2015) A robust and low-complexity source localization algorithm for asynchronous distributed microphone networks [J]. IEEE/ACM Trans Audio Speech Lang Proc 23(10):1563–1575. doi:10.1109/TASLP.2015.2439040
Dai HC, Colin MB (1995) Automatic picking of seismic arrivals in local earthquake data using an artificial neural network. Geophys J Int 120(3):758–774. doi:10.1111/j.1365-246X.1995.tb01851.x
de Souza Faria G, Kim HY (2016) Identification of pressed keys by time difference of arrivals of mechanical vibrations. Comput Security 2016(57):93–105. doi:10.1016/j.cose.2015.11.002
Du H (2015) The design of a new type of TDOA-based local space mouse. IEEE International Conference on Mechatronics and Automation, Beijing, 1755–1760. doi:10.1109/ICMA.2015.7237751
Du YS, Wei P, Zhang HG (2015) Semidefinite programming approach for TDOA/GROA based source localization. J Syst Eng Elect 26(4):680–687. doi:10.1109/JSEE.2015.00075
Gambi JM, Rodríguez-Teijeiro MC, Pino MLGD (2016) Newtonian and post-Newtonian passive Geolocation by TDOA. Aerosp Sci Technol 51:18–25. doi:10.1016/j.ast.2016.01.016
Guohui ZHU, Dazheng FENG, Hu XIE et al (2016) An approximately efficient bi-iterative method for source position and velocity estimation using TDOA and FDOA measurements. Sig Process 2016(125):110–121. doi:10.1016/j.sigpro.2015.12.013
Jihao YIN, Qun WAN, Shiwen YANG et al (2015) A simple and accurate TDOA-AOA localization method using two stations. IEEE Signal Process Lett 23(1):144–148. doi:10.1109/LSP.2015.2505138
Kan Y, Wang PF, Zha FS, Li MT, Gao W, Song BY (2015) Passive acoustic source localization at a low sampling rate based on a five-element cross microphone array. Sensors 15(6):13326–13347. doi:10.3390/s150613326
Lesniak A (2015) Seismic network configuration by reduction of seismic source location errors. Int J Rock Mech Mining Sci 118–128. doi:10.1016/j.ijrmms.2015.09.013
Li N, Ge MC, Wang EY (2015) Two types of multiple solutions for microseismic source location based on arrival-time-difference approach. Nat Hazards 2015:73. doi:10.1007/s11069-014-1110-y
Meng Yufeng, Jiancheng Xu, Yan Huang et al (2015) Key factors of multi-station TDOA passive location study. Int Conf Intell Human Mac Syst Cybernet Hangzhou 2:220–223. doi:10.1109/IHMSC.2015.190
Nan LI, Enyuan WANG, Maochen GE et al (2014) A method for identifying outlier signals for microseismic event based on arrival time difference [J]. Chin J Rock Mech Eng 33(8):1644–1661. doi:10.13722/j.cnki.jrme.2014.08.016
Prange MD, Bose S, Kodio O, Djikpesse HA (2015) An information-theoretic approach to microseismic source location, Geophys J Int 193–206. doi:10.1093/gji/ggv009
Sauer Timothy (2014) Numerical analysis. George Mason University, Fairfax, pp 205–210
Uysal C, Filik, T (2015) A joint detection and localization method for non-cooperative DS-SS signals. IEEE Military Communications Conference, Tampa, FL, 523–528. doi:10.1109/MILCOM.2015.7357496
Xiaomei QU, Lihua XIE (2016) An efficient convex constrained weighted least squares source localization algorithm based on TDOA measurements. Sig Process 2016(119):142–152. doi:10.1016/j.sigpro.2015.08.001
Xionghu Z, James R (2015) Hopgood. A time-frequency masking based random finite set particle filtering method for multiple acoustic source detection and tracking. IEEE/ACM Trans Audio Speech Lang Proc 23(12):2356–2370. doi:10.1109/TASLP.2015.2479041
Xue QF, Wang YB, Zhang Y, Chang X (2015) An efficient GPU implementation for locating micro-seismic sources using 3D elastic wave time-reversal imaging. 89–97. doi:10.1016/j.cageo.2015.05.008
Zhaojun MA, Chang-an DI, Deren KONG et al (2012) Landing point location model based on seismic wave. J Sichuan Ordnance 33(7):20–26
Zhu GH, Feng DZ, Xie H, Zhou Y (2015) An approximately efficient bi-iterative method for source position and velocity estimation using TDOAand FDOA measurements. Sig Proc 110–121. doi:10.1016/j.sigpro.2015.12.013
Author information
Authors and Affiliations
Corresponding author
Additional information
An erratum to this article is available at http://dx.doi.org/10.1007/s00542-016-3227-2.
Rights and permissions
About this article
Cite this article
Li, P., Che, L. Landing point location algorithm based on asynchronous time difference of arrival (ATDOA) method. Microsyst Technol 23, 1475–1484 (2017). https://doi.org/10.1007/s00542-016-3162-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00542-016-3162-2