Precise relative navigation is a critical enabler for distributed satellites to achieve new mission objectives impossible for a monolithic spacecraft. Carrier phase differential GPS (CDGPS) with integer ambiguity resolution (IAR) is a promising means of achieving cm-level accuracy for high-precision Rendezvous, Proximity-Operations and Docking (RPOD), In-Space Servicing, Assembly and Manufacturing (ISAM) as well as satellite formation flying and swarming. However, IAR is sensitive to received GPS signal noise, especially under severe multi-path or high thermal noise. This paper proposes a sensor-fusion approach to achieve IAR under such conditions in two coupling stages. A loose coupling stage fuses through an Extended Kalman Filter the CDGPS measurements with on-board sensor measurements such as range from cross-links, and vision-based bearing angles. A second tight-coupling stage augments the cost function of the integer weighted least-squares minimization with a soft constraint function using noise-weighted observed-minus-computed residuals from these external sensor measurements. Integer acceptance tests are empirically modified to reflect added constraints. Partial IAR is applied to graduate integer fixing. These proposed techniques are packaged into flight-capable software, with ground truths simulated by the Stanford Space Rendezvous Laboratory's S3 library using state-of-the-art force modelling with relevant sources of errors, and validated in two scenarios: (1) a high multi-path scenario involving rendezvous and docking in low Earth orbit, and (2) a high thermal noise scenario relying only on GPS side-lobe signals during proximity operations in geostationary orbit. This study demonstrates successful IAR in both cases, using the proposed sensor-fusion approach, thus demonstrating potential for high-precision state estimation under adverse signal-to-noise conditions.

翻译：精确相对导航是实现分布式卫星完成单体航天器无法实现的新任务目标的关键技术。载波相位差分GPS（CDGPS）结合整周模糊度解算（IAR）是达成厘米级精度的重要途径，广泛应用于高精度交会、近距操作与对接（RPOD）、在轨服务、组装与制造（ISAM）以及卫星编队飞行与集群。然而，IAR对接收到的GPS信号噪声十分敏感，尤其在严重多径或高热噪声条件下。本文提出一种传感器融合方法，通过两个耦合阶段实现上述条件下的IAR。松耦合阶段利用扩展卡尔曼滤波器融合CDGPS测量值与星载传感器测量值（如星间链路测距及基于视觉的方位角）。紧耦合阶段通过引入外部传感器测量值的噪声加权观测残差作为软约束函数，增强整周加权最小二乘最小化的代价函数。对整周验收检验进行经验性改进以反映新增约束，并采用部分IAR实现逐步整周固定。所提技术被封装为具备飞行能力的软件，其真实值由斯坦福空间交会实验室的S3库通过最先进力模型及相关误差源仿真生成，并在两种场景中验证：（1）低地球轨道交会对接的高多径场景；（2）地球静止轨道近距操作中仅依赖GPS旁瓣信号的高热噪声场景。研究表明，所提传感器融合方法在两种场景下均成功实现IAR，从而展示了在不利信噪条件下实现高精度状态估计的潜力。