利用低轨卫星多普勒信号实现无需初始值的可靠定位
Certifiably Optimal Doppler Positioning using Opportunistic LEO Satellites
- 通过凸优化与半定规划实现可验证最优定位
- 实测误差仅140米,且不依赖初始位置
- 适合无先验信息的紧急定位场景
为增强全球导航卫星系统(GNSS)的备份与扩展能力,可利用低地球轨道(LEO)卫星的多普勒频移作为信号机会(SOP)进行定位、导航与授时(PNT)。由于多普勒定位问题非凸,传统局部搜索方法可能陷入局部最优或无法识别全局最优。在缺乏精确初始值的未知环境中,无需初始化的可验证全局优化方法至关重要。本文提出一种可验证最优的LEO多普勒定位方法,基于梯度加权近似(GWA)算法与半定规划(SDP)松弛。在理想无噪声情况下推导出最优性必要条件,在有噪声情况下给出充分噪声边界条件以保证最优性。仿真与实测验证表明,使用Iridium-NEXT卫星的实测结果显示,该方法在无初始估计下实现3D定位误差140米,而高斯-牛顿与Dog-Leg方法在初始点距离真实位置超过1000公里时陷入局部最优;此外,该可验证解可作为局部优化的初始值,进一步将3D误差降至130米。
原文摘要 · Abstract (English)
To provide backup and augmentation to global navigation satellite system (GNSS), Doppler shift from Low Earth Orbit (LEO) satellites can be employed as signals of opportunity (SOP) for position, navigation and timing (PNT). Since the Doppler positioning problem is non-convex, local searching methods may produce two types of estimates: a global optimum without notice or a local optimum given an inexact initial estimate. As exact initialization is unavailable in some unknown environments, a guaranteed global optimization method in no need of initialization becomes necessary. To achieve this goal, we propose a certifiably optimal LEO Doppler positioning method by utilizing convex optimization. In this paper, the certifiable positioning method is implemented through a graduated weight approximation (GWA) algorithm and semidefinite programming (SDP) relaxation. To guarantee the optimality, we derive the necessary conditions for optimality in ideal noiseless cases and sufficient noise bounds conditions in noisy cases. Simulation and real tests are conducted to evaluate the effectiveness and robustness of the proposed method. Specially, the real test using Iridium-NEXT satellites shows that the proposed method estimates an certifiably optimal solution with an 3D positioning error of 140 m without initial estimates while Gauss-Newton and Dog-Leg are trapped in local optima when the initial point is equal or larger than 1000 km away from the ground truth. Moreover, the certifiable estimation can also be used as initialization in local searching methods to lower down the 3D positioning error to 130 m.
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