The tracking and data relay satellite (TDRS) in geosynchronous orbit (GEO) can provide ranging and communication services for user spacecraft in low Earth orbit (LEO) through the inter‐satellite link ...(ISL). The time delay of TDRS ISL transponder in orbit differs from its pre‐launch state and changes due to the complex space environment, adding significant errors to the user spacecraft's orbit determination based on four‐way ranging data. The authors have developed a calibration system and proposed an efficient on‐orbit calibration method for the ISL transponder's time delay in TDRS. Experimental results demonstrate the effectiveness of the authors’ method, and the RMS of calibration residuals is less than 0.5 m.
We have developed a calibration system and proposed an efficient on‐orbit calibration method for the ISL transponder's time delay in TDRS. Experimental results demonstrate the effectiveness of our method, and the RMS of calibration residuals is less than 0.5 meters.
The problem of efficient link selections for cooperative navigation is investigated in dynamic wireless networks, using an extended Kalman filter based overlapping coalition formation (OCF) game ...approach. Due to the densely deployment of nodes without proper link selections, the conventional cooperative navigation approaches usually yield high time‐frequency resources as the existing resource management methods only work properly in static localisation systems. A new link selection mechanism which is reliable with limited resources in dynamic positioning scenarios is proposed. The varying topological structure and states of every node will be taken into consideration while each node abandons a considerable number of unnecessary links. Firstly, the state of every mobile node will be estimated in real‐time. Then a selection criterion is applied to determine whether nodes are well navigated. If the criterion is satisfied, an OCF game will be employed to construct the effective link selection. Otherwise, a re‐link mechanism will be used to obtain precise state information of each node. Numerical results show that the cooperative navigation algorithm can significantly improve the positioning accuracy and the proposed OCF game approach can build a cooperative network with limited number of links at the cost of appropriate performance degradation.
The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the ...minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.
Swarming is one of the important trends in the development of small multi-rotor UAVs. The stable operation of UAV swarms and air-to-ground cooperative operations depend on precise relative position ...information within the swarm. Existing relative localization solutions mainly rely on passively received external information or expensive and complex sensors, which are not applicable to the application scenarios of small-rotor UAV swarms. Therefore, we develop a relative localization solution based on airborne monocular sensing data to directly realize real-time relative localization among UAVs. First, we apply the lightweight YOLOv8-pose target detection algorithm to realize the real-time detection of quadcopter UAVs and their rotor motors. Then, to improve the computational efficiency, we make full use of the geometric properties of UAVs to derive a more adaptable algorithm for solving the P3P problem. In order to solve the multi-solution problem when less than four motors are detected, we analytically propose a positive solution determination scheme based on reasonable attitude information. We also introduce the maximum weight of the motor-detection confidence into the calculation of relative localization position to further improve the accuracy. Finally, we conducted simulations and practical experiments on an experimental UAV. The experimental results verify the feasibility of the proposed scheme, in which the performance of the core algorithm is significantly improved over the classical algorithm. Our research provides viable solutions to free UAV swarms from external information dependence, apply them to complex environments, improve autonomous collaboration, and reduce costs.
In order to solve the problem of decreased navigation performance of the Global Navigation Satellite System (GNSS)/inertial navigation system (INS) integrated navigation systems in GNSS-denied ...environments, and to improve the navigation accuracy and robustness of the navigation system, a novel adaptive federated filter with a feedback scheme for a GNSS/INS/visual odometry (VO) integrated navigation system is proposed in this paper. A visual-inertial odometry system model with a multi-state constraint Kalman filter structure based on a polar geometry and trifocal tensor geometry between different images is established, which can provide better navigation accuracy in GNSS-denied environments. Moreover, a new method to obtain the information allocation factor according to the different navigation performances of local filters is deduced in this paper, which has low computational complexity and a simple structure. Meanwhile, an abnormal measurement detection algorithm based on fuzzy logic is proposed to detect the abnormal measurements of local filters. The results of the vehicle experiment with the publicly available real-world KITTI dataset show that the proposed algorithm can obtain reliable navigation results in GNSS-denied environments and improve the navigation accuracy and robustness of the GNSS/INS/VO integrated navigation system.
Consecutively tracking the global navigation satellite system (GNSS) signal can cause power and computation difficulties to a smart GNSS device with small battery capacity and weak computation ...capability. We propose a novel computationally efficient ultra-tight integration of GNSS and inertial navigation system (INS). Rather than be consecutively tracked in the traditional receiver as well as its integration with INS, the GNSS signal is non-consecutively tracked in the proposed ultra-tight integration. Compared to traditional GNSS duty cycling (DC) techniques, the proposed ultra-tight integration does not have a tracking loop inside the receiver baseband and only GNSS code signals are tracked with the assistance of INS. The non-consecutive tracking control methods for the GNSS code signals with different wavelengths are investigated, and a moving window-based method is also designed to monitor the non-consecutive code tracking. To validate the proposed ultra-tight integration, a vehicle-based experiment is performed in which global positioning system (GPS), Galileo and BDS (BeiDou Navigation Satellite System) signals are non-consecutively tracked by a developed multi-constellation and multi-frequency software-defined receiver and ultra-tightly coupled with micro-electro-mechanical system (MEMS) inertial measurement unit (IMU)-based INS. The experiment results show that the proposed ultra-tight integration can significantly reduce system computation burden and power consumption and can get a better navigation solution than traditional GNSS receiver and DC techniques.
In the GNSS/INS integrated navigation system, the accuracy of square-root cubature Kalman filter (SCKF) will be reduced when the process model is not precisely known. To solve this problem, a novel ...strong tracking SCKF is proposed. The proposed algorithm utilises the measurement update module based on singular value decomposition (SVD), which can reduce the computational complexity. Moreover, a novel method to obtain suboptimal fading factor based on the orthogonality of the innovation is deduced here, which is simple to calculate and no need to solve the Jacobian matrix. This novel method introduces the calculated suboptimal fading factor into the square-root of the state prediction covariance matrix. Then, the gain matrix can be adjusted online which can improve the robustness of the algorithm when the process model is uncertain. Meanwhile, the proposed algorithm adopts the hypothesis testing to detect the uncertainty of the process model. Then, the proposed approach will only use the suboptimal fading factor when the existing process model is uncertain. The results of both numerical simulations and the field tests with GNSS/INS integrated navigation system demonstrate the effectiveness of the proposed algorithm.
The precise point positioning (PPP) is widely used as a typical representative of GNSS. But the main challenge of dual-frequency PPP is that it requires quite a long time to succeed in the ...ambiguity-fixed so it takes more than 30 min to obtain centimeter-level accuracy. A combination of GPS and low earth orbit (LEO) satellites can improve the diversity of available satellites' geometric distribution and reduce the correlation of observation data between epochs. Then the accuracy of float solution will be promoted and the ambiguity of GPS will take less time to get fixed. The purpose of this paper is to reduce the convergence time of PPP by the contribution of LEO satellites which have low earth orbit and move speedily. We adopt a free-ionosphere PPP model to combine GPS and LEO satellites. Numerous experimental results show that GPS/LEO PPP requires much less convergence time and gets higher positioning accuracy than that of PPP with GPS alone. In addition, an analysis is also made to compare GPS/LEO PPP and GPS/GLONASS PPP. The results indicate that GPS/LEO PPP also requires much less convergence time and gets higher positioning accuracy than that of GPS/GLONASS PPP when increasing the same number of available satellites. This proved that LEO satellites have more contribution to PPP performance than MEO.
This paper reports an application of inertial sensors based on a brand-new concept of software-defined inertial (SDI). The idea is aiming at unfolding inertial sensors' signal processing domain to ...the customers for integrating external information into the inertial sensor's signal processing part to improve the performance of the inertial sensors and the integration system. The implementation of the software-defined gyroscope (SDG) reported in this paper is the first attempt to use the software architecture to process the signals inside the inertial device. Such a structure would bring lots of benefits, including performance improvement of inertial sensors and flexible signal processing parameter adjustment. By employing the Allan Variance method, this paper reveals the relationship between the signal processing process and the random characteristics of inertial sensors, which is critical for applications such as GPS/INS integrated systems. We show that different signal processing strategies would result in different stochastic error characteristics for the inertial sensors. Thus, we believe that the contribution of this paper can be good guidance for more advanced integrated system designs using software-defined inertial sensors.
Global satellite navigation system (GNSS) is the most commonly used navigation and positioning system for its superior performance and low cost of the terminal receiver. However, in some scenarios, ...when the navigation signal is obscured or interfered, GNSS may lose its superior performance, even becomes unusable. Extending the integration time is a general way to enhance the receivers' usability. Commonly, this method requires assistance data from somewhere else, a ground wireless sensor network as an example, and a stable oscillator. In this paper, we try to remove such assistance restricts. With some acceptable assumptions, we can calculate the frequency instability of the GNSS receiver's reference oscillator. Thus we can extend the integration time by the application of this frequency stability transfer strategy and finally acquired the weak navigation signals.
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