随钻测斜用微小型导航计算机系统设计与实现

为了满足随钻测斜仪器在油气井中恶劣环境下的测量要求,本文提出了一种以数字信号控制器（DSC）和FPGA组成的双CPU导航计算机方案。该系统由DSC（dsPIC30F6014A）作为核心处理器完成导航计算和滤波算法;由FPGA完成对IMU（惯性测量单元）数据的采集控制及传输等功能。DSC与FPGA之间通过串口传输,最终导航结果由DSC输出给外部控制设备。该系统很好的满足了随钻测斜仪的性能尺寸要求,试验验证结果表明倾斜角、方位角、和工具面角均达到了预期精度指标。     

基于鲁棒扩展卡尔曼滤波的双目视觉测量相对导航技术研究

针对非合作目标相对导航问题,为提高相对导航的精度和可靠性,采用双目视觉测量方法实现追踪器与目标器之间相对状态的测量,并基于鲁棒扩展卡尔曼滤波方法,提出了一种鲁棒相对导航滤波方法。仿真结果表明,该方法对相对导航系统模型中的不确定性具有良好的鲁棒性,且滤波精度较高。     

基于卫星授时控制器的设计与实现

针对一些小型试验场或舰船上的条件局限性,对授时、控制等参试设备提出了更高的要求,希望提供一种功能全面、携带方便的小型化设备,用以满足试验的多种需求.为解决这个问题,研制了新一代时统设备——卫星授时控制器.基于GPS（全球定位系统）/BDS-Ⅱ（“北斗”二代）卫星授时原理,采用功能较强的微控制器和可编程器件产生多种时频信号、控制信号和模拟导航信息,实现了定时、控制、接收和产生等多重功能,提高了设备的集成性、通用性和便携性;同时采用倍频、锁相、驯服等技术,使设备10 MHz频率源的准确度提高2个量级,卫星同步精度优于50 ns.该控制器已成功应用于移动测控站和舰船试验中,效果良好.     

无人机地面站人机工效综合评价研究

无人机地面站发展日趋综合复杂,为了减轻地面站操作员工作负荷,避免飞行事故发生,保证高效、安全地完成飞行任务,开展无人机地面站人机工效评价方法研究十分重要.分析无人机地面站人机工效评价特点;借鉴有人驾驶飞机人机工效评价力法,利用德尔菲法,明确无人机地面站人机工效综合评价的评价指标,提出地面站人机工效评价专家调查表的构架及其内容;并探索无人机地面站人机工效评价方法.实例研究表明：本文提出的评价指标和方法可以满足无人机地面站人机工效评价需求,可为无人机地面站人机工效评价提供一定借鉴.     

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.     

综合通信导航识别系统的故障注入方法研究

针对综合通信导航识别系统的综合化、模块化特点，在综合分析系统故障检测诊断机制、构建系统故障信息库的基础上，设计了一种面向综合通信导航识别系统的软件故障注入方案，可提高综合通信导航识别系统故障诊断软件的效能。通过利用此方案进行故障注入试验，验证了综合通信导航识别系统故障诊断软件的功能和性能。     

Dual smoothing ionospheric gradient monitoring algorithm for dual-frequency BDS GBAS

In this study, a Dual Smoothing Ionospheric Gradient Monitor Algorithm (DSIGMA) was developed for Code-Carrier Divergence (CCD) faults of dual-frequency Ground-Based Augmentation Systems (GBAS) based on the BeiDou Navigation Satellite System (BDS). Divergence-Free (DF) combinations of the signals were used to form test statistics for a dual-frequency DSIGMA. First, the single-frequency DSIGMA was reviewed, which supports the GBAS approach service type D (GAST-D) for protection against the effect of large ionospheric gradients. The single-frequency DSIGMA was used to create a novel input scheme for the dual-frequency DSIGMA by introducing DF combinations. The steady states of the test statistics were also analysed. The monitors were characterized using BDS measurement data, whereby standard deviations of 0.0432 and 0.0639 m for the proposed two test statistics were used to calculate the monitor threshold. An extensive simulation was designed to assess the monitor performance by comparing the Probability of Missed Detection (PMD) according to the differential error with the range domain PMD limits under different fault modes. The results showed that the proposed algorithm has a higher integrity performance than the single-frequency monitor. The minimum detectable divergence with the same missed probability is less than 50% that of GAST-D.     

Modeling and analysis of solar Doppler difference bias with arbitrary rotation axis

The solar rotation causes the solar Doppler difference bias, which leads to the decline of the velocity measurement accuracy. Modeling and compensation are an effective solution. The limited model with specific geometric direction, where the solar rotation axis is perpendicular to the plane through the Sun, the Earth and Mars, was established. However, in fact, the geometric relationship among the Sun, Mars and the spacecraft is not fully in line with the hypothesis of the model due to the spacecraft orbital angle and the solar rotation axis drift. Thus, this model is not consistent with the fact. In order to solve this problem, a universal solar Doppler difference bias model, which provides the expression with arbitrary rotation axis, is established in this paper. In this method, for any point at the solar surface, four variables including the direction of the solar rotation linear velocity at this point, the distance from this point to the rotation axis, the vector from this point to Mars, and the vector from this point to the spacecraft are calculated. Based on these four variables, the solar Doppler difference bias corresponding to this point is obtained. The theoretical analysis and simulation results demonstrate that the solar Doppler difference bias model with the actual rotation axis is different from that with one of the specific rotation axes. Therefore, it is indispensable to build the proposed model for compensation. Besides, the direction of the solar rotation axis, the spacecraft-Mars-Sun angle and the spacecraft-to-Mars distance are important impact factors for the proposed model.     

Concurrent image-based visual servoing with adaptive zooming for non-cooperative rendezvous maneuvers

An image-based servo controller for the guidance of a spacecraft during non-cooperative rendezvous is presented in this paper. The controller directly utilizes the visual features from image frames of a target spacecraft for computing both attitude and orbital maneuvers concurrently. The utilization of adaptive optics, such as zooming cameras, is also addressed through developing an invariant-image servo controller. The controller allows for performing rendezvous maneuvers independently from the adjustments of the camera focal length, improving the performance and versatility of maneuvers. The stability of the proposed control scheme is proven analytically in the invariant space, and its viability is explored through numerical simulations.     

Deep reinforcement learning for six degree-of-freedom planetary landing

This work develops a deep reinforcement learning based approach for Six Degree-of-Freedom (DOF) planetary powered descent and landing. Future Mars missions will require advanced guidance, navigation, and control algorithms for the powered descent phase to target specific surface locations and achieve pinpoint accuracy (landing error ellipse <5 m radius). This requires both a navigation system capable of estimating the lander’s state in real-time and a guidance and control system that can map the estimated lander state to a commanded thrust for each lander engine. In this paper, we present a novel integrated guidance and control algorithm designed by applying the principles of reinforcement learning theory. The latter is used to learn a policy mapping the lander’s estimated state directly to a commanded thrust for each engine, resulting in accurate and almost fuel-optimal trajectories over a realistic deployment ellipse. Specifically, we use proximal policy optimization, a policy gradient method, to learn the policy. Another contribution of this paper is the use of different discount rates for terminal and shaping rewards, which significantly enhances optimization performance. We present simulation results demonstrating the guidance and control system’s performance in a 6-DOF simulation environment and demonstrate robustness to noise and system parameter uncertainty.