![]() scenarios: (a) without a calibration emitter (b) with a single calibration emitter whose position is subject to measurement errors (c) with a single calibration emitter whose position is perfectly known, and (d) with a single calibration emitter, whose position is completely unknown. A semidefinite programming (SDP) technique to effectively transform the MLE problem into a convex optimization is proposed, together with a unified solution for four. This technique starts with maximum likelihood estimation (MLE), which is known to be nonconvex. This paper develops a unified solution for time-difference-of-arrival (TDOA) localization in the presence of sensor position errors. ©, 2015, Chinese Institute of Electronics. The simulation result shows the proposed algorithm can effectively compensate the target height information and obtain the stable and reliable estimation of the target space state, which can be used in the actual projects as the effective and perfect method for the target space state estimate problem of the 2-D radar. At last, combining the original measurement equation of the 2-D radar with the target height estimation equation and using extended Kalman filter, the target space state was estimated. And the error in the formula was calculated using absolute value inequality and Cauchy-Schwarz inequality. Then utilizing identical transformation and reasonable approximations, an approximate estimation formula of the target height was derived. First, on the basis of the transformation relation between different coordinates, an exact formula of the target height was deduced. To avoid these defects, the problem of tracking the aerial target in 3-D space with a 2-D radar was restudied under the assumption that the target flights at a constant speed and a fixed altitude and the radar can obtain the indication information of the target from other collaborative detect units. There are some shortcomings in the existing target height compensation algorithms, such as unreasonable model assumptions and unstable application effect. ![]()
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