Four-wheel independently driven skid steer robotic vehicles (IDSSRVs) have been widely applied in many fields. However, limited by small size and low power consumption, many sensors and high-performance processors cannot be equipped into four-wheel IDSSRVs, which makes path tracking more complex. The nonsingular terminal sliding mode (NTSM) is a good choice for small robotic vehicles because of its strong robustness, fast convergence and low complexity. However, the performance of the NTSM is easily affected by vehicular weight and road friction, because a four-wheel IDSSRV has no steering devices and its driving behavior is completed by adjusting the velocity of the four wheels based on the wheel-ground interaction. Furthermore, a minor instability caused by the output difference of the motors can bring an extra torque on the vehicle and ultimately lead to a tracking deviation for the NTSM controller. To resolve these problems, a dynamic model of a four-wheel IDSSRV is analyzed first. Subsequently, a cascaded NTSM-PID method is proposed, in which a conversion function based on compensating the sideslip angle is raised to improve the NTSM controller performance of anti-disturbance and tracking accuracy with the limitations of the sensors and processors, and a joint PID controller simultaneously optimizing the motor output error and vehicular yaw error is designed to eliminate the imbalance of motor output and to reduce the deviation of the NTSM controller. Finally, comparative experiments are conducted, and the results highlight the benefits of the proposed approach by reducing the tracking error by approximately 80% compared with the dynamic MPC method and reducing the tracking error by over 30% compared with the pure NTSM method.

The Global Navigation Satellite System (GNSS) observations with global coverage and high temporal and spatial resolution, provide abundant and high-quality Earth-ionosphere observations. By calculating the total electron content (TEC), estimations from GNSS observables global and regional ionosphere TEC morphology can be further investigated. For the multiple constellation case, the numbers of ionosphere pierce points (IPP) has increased tremendously, and it is worth studying the features of the GNSS derived TEC under geomagnetic storms to show the benefits of multiple constellation measurements. With the Multi-GNSS Experiment (MGEX) observation data, ionosphere TEC responses to the geomagnetic storm on the 22 June 2015 were well studied. TEC perturbations were discovered, accompanied by ionosphere irregularities concentrating in high and middle latitudes. Through analysis of multi-GNSS observations, the Rate of TEC Index (ROTI) perturbations were proved to be generated by the geomagnetic storm, with simultaneous behaviors at different local times around the world, also indicating ionosphere scintillation. The ionosphere spatial gradient was also discussed with two short baseline MGEX sites; the maximum ionosphere gradient of 247.2 mm/km was found, due to ionosphere irregularity produced by the storm. This research has discussed ionosphere responses to geomagnetic storms with multi-GNSS data provided and has analyzed the availability of multi-GNSS observations to investigate ionosphere irregularity climatology. The proposed work is valuable for further investigation of GNSS performances under geomagnetic storms.

The fiber optic gyroscope (FOG) suffers from the excess relative intensity noise (RIN) caused by the broadband light source, which significantly impacts the angular random walk (ARW) of the FOG. The existing suppression methods for the excess RIN usually require complex configuration or devices with big volume, and thus are not suitable for practical applications especially in small-sized FOGs. What is more, as the key parameters or components, that determine the practical suppression effects of the excess RIN, and the corresponding impacting mechanisms are not clarified, there is no efficient way in evaluating or optimizing the excess-RIN reduction configuration in practice. In this work, we propose a simple but effective method to achieve the reduction of the excess RIN at the demodulation frequency, in which a Faraday rotator mirror is inserted to the dead arm of the source coupler to realize the delay line filter for the excess RIN. Experimental results show that the ARW is improved from 1.70 mdeg/h^1/2 to 0.58 mdeg/h^1/2 for a navigation-grade FOG. More importantly, this work provides a comprehensive understanding on how the main defects in the excess-RIN reduction scheme impact the practical excess-RIN suppression effects both theoretically and experimentally, which demonstrates the inherent robustness of the proposed scheme against internal and external influencing factors. This method is especially suitable for realizing the excess-RIN reduction in small-sized FOGs and upgrading the existing FOG products with minimal modifications, and is also potentially referable in evaluating and optimizing other similar excess-RIN reduction schemes.

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.

Strap-down inertial navigation systems (INSs) with quartz flexible accelerometers (QFAs) are widely used in many conditions, particularly in aerial vehicles. Temperature is one of the significant issues impacting the performance of INS. The variation and the gradient of temperature are complex under aerial conditions, which severely degrades the navigation performance of INS. Previous work has indicated that parts of navigation errors could be restrained by simple temperature compensation of QFA. However, the temperature hysteresis of the accelerometer is seldom considered in INS. In this paper, the temperature hysteresis mechanism of QFA and the compensation method would be analyzed. Based on the fundamental model, a comprehensive temperature hysteresis model is proposed and the parameters in this model were derived through a temperature cycling test. Furthermore, the comparative experiments in the laboratory were executed to refine the temperature hysteresis model and to verify the effectiveness of the new compensation method. Applying the temperature hysteresis compensation in flight condition, the result shows that the position error (CEP) is restrained from 1.54 nmile/h to 1.29 nmile/h. The proposed temperature hysteresis compensation method improves the performance of INS effectively and feasibly, which could be promoted to other applications of INS in similar temperature changing environment correspondingly.

Vehicle-to-everything communication (V2X) and mobile edge computing (MEC) have introduced significant technological innovations for autonomous ground vehicles (AGVs), enabling most driving task computations to be performed with edge servers with higher quality and effectively reducing computational power consumption for AGVs. For reducing more computational power consumption which can reach hundreds of watts, sending more offloading tasks to edge servers can result in high latency and congestion when the network resources are finite and even cause serious traffic accidents. Besides, in V2X network, multiple transmission paths, including vehicle-to-vehicle (V2V) links and vehicle-to-infrastructure (V2I) links, can provide more valuable resources for sending offloading tasks, but they increase the complexity of resource management. To improve the utilization efficiency of network resources and ensure low power consumption for AGVs, first, this paper analyzes mathematical models of bandwidth, delay and power consumption based on different computing modes and transmission paths. Second, we propose an allocation algorithm for network resource allocation, transmission paths and computing modes to minimize power consumption according to the states of the V2X-MEC network measured and predicted by the navigation and positioning system. Third, a traversal approach simplified by a road segmentation method is adopted to solve for the optimal parameters. Through simulations, we compare our solution against an allocation approach based on the shortest path method, minimum average delay method and game theory method to illustrate the effectiveness of our proposed method in reducing the power consumption and transmission delay of uplinks.