WGS-84模型下时差频差半定规划定位算法
收稿日期: 2016-10-12
修回日期: 2016-11-28
网络出版日期: 2017-04-01
基金资助
气象信息与信号处理四川省高校重点实验室基金
Semidefinite programming algorithm with TDOA and FDOA measurements based on WGS-84 earth model
Received date: 2016-10-12
Revised date: 2016-11-28
Online published: 2017-04-01
Supported by
Meteorological Information and Signal Processing Key Laboratory of Sichuan Higher Education Institutes
李万春 , 彭吴可 , 彭丽 , 马叶子 , 李英祥 . WGS-84模型下时差频差半定规划定位算法[J]. 航空学报, 2017 , 38(7) : 320843 -320843 . DOI: 10.7527/S1000-6893.2017.320843
In essence, detecting the location and velocity of a radiation source by utilizing time difference of arrival/frequency difference of arrival (TDOA/FDOA) for multiple satellites can be deemed as a highly nonlinear solution problem within noise. For a ground target, the WGS-84 earth model is the constraint condition, which makes the location system become more complicated. In this paper, a new algorithm for solving this location problem is proposed based on the semi-definite programming (SDP). Based on the novel algorithm, the nonlinear location problem can turn into a semidefinite optimization (SDO) by an appropriate relaxation which can be solved by some mature software like CVX. According to this model, the Cramer-Rao Lower Bound (CRLB) of the location problem is then given. The computer simulation demonstrates that the proposed algorithm can approach the CRLB effectively.
[1] HO K C, XU W. An accurate algebraic solution for moving source location using TDOA and FDOA measurements[J]. IEEE Transactions on Signal Processing, 2004, 52(9): 2453-2463.
[2] HO K C, CHAN Y T. Geolocation of a known altitude object from TDOA and FDOA measurements[J]. IEEE Transactions on Aerospace & Electronic Systems, 1997, 33(3): 770-783.
[3] 叶尚福, 孙正波, 夏畅雄. 卫星干扰源双星定位技术及工程应用[M]. 北京: 国防工业出版社, 2013: 61-99. YE S F, SUN Z B, XIA C X. Satellite interference location technology and engineering application[M]. Beijing: National Defense Industry Press, 2013: 61-99 (in Chinese).
[4] HO K C, LU X, KOVAVISARUCH L. Source localization using TDOA and FDOA measurements in the presence of receiver location errors: Analysis and solution[J]. IEEE Transactions on Signal Processing, 2007, 55(2): 684-696.
[5] SUN M, HO K C. An asymptotically efficient estimator for TDOA and FDOA positioning of multiple disjoint sources in the presence of sensor location uncertainties[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 3434-3440.
[6] WEI H W, PENG R, WAN Q, et al. Multidimensional scaling analysis for passive moving target localization with TDOA and FDOA measurements[J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1677-1688.
[7] YANG K, JIANG L, LUO Z Q. Efficient semidefinite relaxation for robust geolocation of unknown emitter by a satellite cluster using TDOA and FDOA measurements[C]//IEEE International Conference on Acoustics, Speech and Signal Processing, 2011: 2584-2587.
[8] KIM Y H, HAN J W, SONG K H, et al. Emitter location based on the linearization of quadratic TDOA and FDOA curves[C]//International Conference on Electronics, Information and Communications, 2014: 1-2.
[9] QUO F, HO K C. A quadratic constraint solution method for TDOA and FDOA localization[C]//IEEE International Conference on Acoustics, Speech and Signal Processing, 2011: 2588-2591.
[10] ICKI D, KAUNE R, KOCH W. Mobile emitter geolocation and tracking using TDOA and FDOA measurements[J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1863-1874.
[11] VAGHEFI R M, BUEHRER R M. On the CRLB of TDOA/FDOA estimation from MIMO signals[C]//IEEE/ION Position, Location and Navigation Symposium-PLANS, 2016: 772-778.
[12] TAKABAYASHI Y, MATSUZAKI T, KAMEDA H, et al. Target tracking using TDOA/FDOA measurements in the distributed sensor network[C]//IEEE Xplore Sice Conference, 2008: 3441-3446.
[13] ZHANG W, ZHANG G, HU J. Rrsearch on priori information of TDOA/FDOA in satellite communication based on ephemeris of satellite[C]//IEEE International Conference on Signal Processing, Communications and Computing, 2011: 1-4.
[14] YANG K, WANG G, LUO Z Q. Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals[J]. IEEE Transactions on Signal Processing, 2009, 57(7): 2775-2784.
[15] BISWAS P, LIAN T C, WANG T C, et al. Semidefinite programming based algorithms for sensor network localization[J]. ACM Transactions on Sensor Networks, 2006, 2(2): 188-220.
[16] WANG G. A semidefinite relaxation method for energy-based source localization in sensor networks[J]. IEEE Transactions on Vehicular Technology, 2011, 60(5): 2293-2301.
[17] WANG G, LI Y, ANSARI N. A semidefinite relaxation method for source localization using TDOA and FDOA measurements[J]. IEEE Transactions on Vehicular Technology, 2013, 62(2): 853-862.
[18] DU Y, WEI P. An explicit solution for target localization in noncoherent distributed MIMO radar systems[J]. IEEE Signal Processing Letters, 2014, 21(9): 1093-1097.
[19] YANG H, CHUN J. An improved algebraic solution for moving target localization in noncoherent MIMO radar systems[J]. IEEE Transactions on Signal Processing, 2016, 64(1): 258-270.
[20] LIANG J, LEUNG C S, SO H C. Lagrange programming neural network approach for target localization in distributed MIMO radar[J]. IEEE Transactions on Signal Processing, 2016, 64(6): 1574-1585.
[21] STOICA P, NG B C. On the Cramer-Rao bound under parametric constraints[J]. IEEE Signal Processing Letters, 1998, 5(7): 177-179.
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