Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2018 Jul 4;18(7):2160. doi: 10.3390/s18072160.
Vehicles driving in urban canyons are always confronted with a degraded Global Navigation Satellite System (GNSS) signal environment. The surrounding obstacles may cause signal reflections or blockages, which lead to large multipath noises and intermittent GNSS reception. Under these circumstances, it is not feasible to use conventional real-time kinematic (RTK) algorithms to maintain high-precision performance for positioning. In order to meet the special requirements of safety-critical applications under non-ideal observation conditions, a novel tightly coupled RTK/Inertial Navigation System (INS) algorithm is proposed in this paper, which can provide accurate and reliable positioning results continuously. Our integrated RTK/INS algorithm has three features. Firstly, INS measurements are used to help search for integer ambiguities in the position domain. INS solutions can provide a more accurate initial location and a more efficient search region. Secondly, the criterion for determining whether a candidate position is the correct solution is only related to the fractional value of the carrier-phase measurement. Thus, the new algorithm is immune to cycle slips as well as large pseudorange noises. Thirdly, our algorithm can provide more accurate ranging information than the pseudorange, even though it may not necessarily be fixed successfully, because it selects the weighted ambiguity solution as the result rather than the candidate point with maximum probability. The proposed algorithm is demonstrated on both simulated and real datasets. Compared with single epoch RTK and conventional tightly coupled RTK/INS integrations that search integer ambiguities in the ambiguity domain, our method attains better accuracy and stability in a simulated environment. Moreover, the real experimental results are presented to validate the performance of the new integrated navigation algorithm.
在城市峡谷中行驶的车辆总是面临着退化的全球导航卫星系统 (GNSS) 信号环境。周围的障碍物可能会导致信号反射或阻挡，从而导致大的多径噪声和间歇性的 GNSS 接收。在这种情况下，使用传统的实时动态 (RTK) 算法来保持高精度的定位性能是不可行的。为了满足非理想观测条件下安全关键应用的特殊要求，本文提出了一种新的紧耦合 RTK/惯性导航系统 (INS) 算法，该算法可以连续提供准确可靠的定位结果。我们的集成 RTK/INS 算法具有三个特点。首先，利用 INS 测量值帮助在位置域中搜索整周模糊度。INS 解可以提供更准确的初始位置和更有效的搜索区域。其次，确定候选位置是否为正确解的标准仅与载波相位测量的小数部分有关。因此，新算法不仅对周跳，而且对大伪距噪声具有免疫能力。第三，即使伪距不一定能成功固定，我们的算法也能提供比伪距更准确的测距信息，因为它选择加权模糊度解作为结果，而不是选择最大概率的候选点。在模拟和真实数据集上对所提出的算法进行了验证。与在模糊域中搜索整周模糊度的单历元 RTK 和传统的紧耦合 RTK/INS 集成相比，该方法在模拟环境中具有更好的精度和稳定性。此外，还提出了真实实验结果来验证新的组合导航算法的性能。
