Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are present...Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are presented.The necessary condition is expressed without dual variables.The relations between the global optimal solutions of nonconvex quadratic 0-1 problems and the associated relaxed convex problems are also studied.展开更多
非视距(non-line-of-sight,NLOS)误差是导致室内定位精度低、稳定性差的一个重要原因,现有NLOS误差抑制算法存在复杂度较高、鲁棒性较差等问题。提出一种基于凸优化方法的室内NLOS误差抑制算法,为保证定位鲁棒性,该算法先给出鲁棒最小二...非视距(non-line-of-sight,NLOS)误差是导致室内定位精度低、稳定性差的一个重要原因,现有NLOS误差抑制算法存在复杂度较高、鲁棒性较差等问题。提出一种基于凸优化方法的室内NLOS误差抑制算法,为保证定位鲁棒性,该算法先给出鲁棒最小二乘(robust least squares,RLS)形式的位置估计问题,再依据遮挡情况不同,将定位环境分为轻微遮挡环境和严重遮挡环境,并根据两种环境NLOS误差特性,引入新的松弛条件,将上述位置估计问题分别转化为二次约束二次规划问题和二阶锥规划问题并求解。仿真实验表明,相比已有算法,在不同应用场景下,所提算法提高了定位精度,并且有效降低了无解个数,增强了鲁棒性。展开更多
文摘Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are presented.The necessary condition is expressed without dual variables.The relations between the global optimal solutions of nonconvex quadratic 0-1 problems and the associated relaxed convex problems are also studied.
文摘非视距(non-line-of-sight,NLOS)误差是导致室内定位精度低、稳定性差的一个重要原因,现有NLOS误差抑制算法存在复杂度较高、鲁棒性较差等问题。提出一种基于凸优化方法的室内NLOS误差抑制算法,为保证定位鲁棒性,该算法先给出鲁棒最小二乘(robust least squares,RLS)形式的位置估计问题,再依据遮挡情况不同,将定位环境分为轻微遮挡环境和严重遮挡环境,并根据两种环境NLOS误差特性,引入新的松弛条件,将上述位置估计问题分别转化为二次约束二次规划问题和二阶锥规划问题并求解。仿真实验表明,相比已有算法,在不同应用场景下,所提算法提高了定位精度,并且有效降低了无解个数,增强了鲁棒性。
