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In dense networks, the tremendous computational complexity and communication overhead of cooperative localisation are the two main bottlenecks that limit practical application. In this study, we introduce a bootstrap percolation scheme into Gaussian message passing-based cooperative localisation for precise positioning, aimed at reducing the system overhead. Considering the uncertainty information and geometric distribution of neighbours, an approximate collinear detection criterion is proposed to detect the possible flip ambiguities in cooperative localisation. According to the detection result and our connection constraint, agents are divided into three categories and are approximated by different distribution families. A message passing rule is designed to control the propagation direction from high precision to low precision, thereby mitigating potential error propagation. Additionally, a layer-by-layer positioning mechanism is established where the agents are located gradually. Analytical and simulation results indicate that when the ranging standard deviation is 0·2 m, 89·3% of the agent nodes can be located within 0·4 m using the proposed algorithm. Compared with the Hybrid Sum-Product Algorithm over A Wireless Network (H-SPAWN), this ratio is increased by 8·4% and the computational complexity is reduced by 72%.

Cooperative localization is an attractive method to improve both the coverage and accuracy of the positioning systems in GNSS-challenged environments. However, as the number of agents increases, the computational complexity and communication overhead increase dramatically, which are two main bottlenecks of its application in a practical system. In this paper, we focus on reducing the system overhead of the message passing-based cooperative localization algorithm in dense wireless networks. Weighted samples are used to represent the salient characteristics of the local message, and a Gaussian parametric message passing rule is designed to reduce the burden of the network traffic. A relative spatial relationship between the target and its neighbor anchor nodes is proposed to concentrate the samples where the messages have significant mass. Based on the equivalent Fisher information matrix, a node selection scheme is put forward to refine the most contributing link combination for the position. Then, an efficient message calculation method which exploits the Taylor expansion to reduce the system overhead is deduced. The convergence property of the proposed algorithm is further analyzed. Simulation results show that the proposed algorithm leads to excellent performance at the communication overhead and computational complexity, with small losses in localization accuracy.

In the Global Navigation Satellite System (GNSS), the multipath error affected by many aspects is the main error source that affects satellite navigation, and it is difficult to establish a much more accurate model to analyze it. Based on the ground multipath reflection model, it firstly deeply studies the influence of GNSS satellite orbit parameters on multipath fading frequency and establishes a multipath signal model related to satellite orbit parameters. Secondly, the influence of carrier phase cycle slip, receiver clock adjustment, and GNSS satellite orbit on multiparameter- (MP-) combined observations is analyzed in detail based on the measured data. Finally, aiming at the common phenomenon of code-carrier divergence in the Beidou system, the elevation-based pseudorange correction model and a sidereal filtering are built to correct the MP errors; experiments with measured data show that there is a fluctuation range reduction of 35.7% after sidereal filtering when the receiver reaches a steady state.

UWB is especially suitable for indoor positioning because of its strong anti-interference ability, it can achieve centimeter-level positioning accuracy in the line of sight (LOS)environment, but it is challenging to construct a robust and high-precision algorithm in complex and changeable environments. Therefore, we establish a UWB positioning model based on time difference of arrival (TDOA), discuss the iterative principle of standard Kalman filter (SKF) and two improved Kalman filter methods, based on dropped measurements method (SKF-DMM) and global offset method (SKF-GOM) respectively. Simulation results show that: in the NLOS environments, the positioning performance of SKFDMM algorithm is obviously superior to that of SKF and SKFGOM, which can improve the robustness and adaptability of UWB indoor positioning system to the complex environments.

Multivariate organic acids can modify the structure and morphology of materials to some extent. In this work, the addition of oxalic acid can make the morphology of ZnIn2S4 become uniform, the crystal structure of ZnIn2S4 can change from cubic to hexagonal, and the photocatalytic activity was improved. The dual Z-scheme ZnIn2S4/BiOCl heterojunction was successfully fabricated by a two-step hydrothermal-hydrolytic method. The concept of green chemistry was used to make full use of thiourea, and the rapid decomposition of Rh B and TC was realized by ZIS/BOC-8 under visible light in a shorter period time than other photocatalysts in this system. In order to investigate the relationship between the structure and properties of the catalyst, XRD, FT-IR, SEM, HRTEM, UV–vis DRS, XPS and other characterization technologies were used to analyze the structure, morphology, optical properties of the samples, showing that ZnIn2S4/BiOCl have been successfully synthesized indicates the existence of Z-scheme heterojunction structure. PL, TRPL and EIS analysis showed that the Z-scheme heterostructures could rapidly promote the separation of holes and photo-induced electron carriers, enhancing the photocatalytic performance and stability. The photocatalytic degradation results showed that the degradation rate of Rh B and TC by ZIS/BOC-8 were more than 92% within 30 min, comparing with other catalyst, ZIS/BOC-8 showed preferable visible light catalytic degradation activity, and the order of catalytic activity was as follows: ZIS/BOC-8 > BiOCl-S > BiOCl, ZnIn2S4. Moreover, the degradation pathway of Rh B was discussed by 3D-EEM and LC-MS, and the photocatalytic mechanism of the system was proposed, especially the mechanism of photocatalytic degradation of Rh B by ZIS/BOC under visible light.

Interconnected three-dimension (3D) networks of novel helical carbon nanotubes (HCNTs) wrapped with reduced graphene oxide nanosheets (HCNTs/rGO) are successfully fabricated via a facile solution of self-assembly method, as well as a robust process for the simultaneous reduction and high N-doping of HCNTs/rGO composites (N-HCNTs/rGO) by photoreduction under NH3 atmosphere. The as-prepared N-HCNTs/rGO are directly employed as binder-free supercapacitor electrodes, and exhibit a highly conductive 3D-interconnected structure (5.85 S cm−1), large surface area (528.9 m2 g−1), low internal resistance (0.5 Ω), and good wettability. As a result, N-HCNTs/rGO show high specific capacitance (368 F g−1), high energy density (12.8 Wh kg−1), and cycling stability (90.7% retention at 1 A g−1 for 5000 cycles) in two-electrode systems. Moreover, the 3D N-HCNTs/rGO hybrid networks exhibit enhanced electrochemical performance in supercapacitors, which combine the synergistic effects of the two carbon nanostructures, enhanced wettability, low internal resistance, and improved ion-diffusion ability, together with the large surface areas of 3D hybrid networks and high-level N-doping. The as-synthesized composite is a potential candidate for flexible and binder-free electrodes for high-performance supercapacitors.

Metadata is the most important application format in current digital book resources. This paper mainly studies the key technologies and applications of metadata extraction in digital books, and proposes a metadata extraction method using information compensation from web. Experiments show that this method can correct errors of the original extracted metadata to a certain extent, and can also complement the missing metadata.

The traditional positioning system based on Global Positioning System (GPS) has provided a lot of convenience for people in the outdoor environment. With the continuous improvement of people's living standards in recent years, the indoor location is more and more popular in intelligent shopping malls and intelligent campus. The traditional GPS location accuracy is limited, so it cannot be used indoor. At present, indoor location technology mainly includes infrared, Bluetooth, Wi-Fi and wireless location which relates to indoor mobile network. Among them, wireless location technology is a research hotspot. Least Squares (LS) method, Chan algorithm and Taylor algorithm based on TDOA in UWB indoor positioning technology are analyzed and tested with dynamic and static data in indoor line-of-sight environment. Results show that the three positioning algorithms can achieve decimeter-level positioning accuracy, and the Taylor algorithm can achieve a 1-decimeter positioning accuracy.

Aiming at the problems that, it is difficult for the administrator to obtain various state information in the forest in real time, and it is impossible to make real-time and accurate judgments on the behaviors that endanger the forest and formulate effective countermeasures, a forest security guard service system based on Beidou positioning is designed. The system adopts STM32F103C8T6as the main control chip to control different types of sensors such as flame sensor, temperature sensor, humidity sensor, sound sensor and so on, the information of temperature, humidity, illumination, fire situation, animal type, personnel alarmaround the nodes in the forest environment associated with the location information of the Beidou module is transmitted to the server through the GPRS network in real-time, then the server broadcasts the normal information and the alarm information to the administrator through the control panel and the mobile client. The system adopts solar energy and can monitor the forest environment information automatically, which can greatly reduce the workload of the employees, low the costs of the network’s layout and monitoring, and provide the researchers with massive and reliable research data. It has a wide range of application in the forest management, agricultural monitoring, environmental monitoring and other fields.

To solve the problem of Ultra-wideband (UWB) TW-TOA ranging accuracy influenced by multipath and non-line-of-sight(NLOS) errors in indoor environment, the performance of UWB signal in indoor NLOS propagation environment is firstly analyzed, and then based on the basic Kalman filter, a two-state Kalman filter algorithm is proposed, which ajusts the Kalman filter gain according to the size of the residual error. If the filter residual is greater than the threshold, the UWB signal is judged as a NLOS signal and the filter gain is set to zero, and replace the current state estimate with a state prediction, otherwise, the basic Kalman filter algorithm is used. Finally, the UWB performance of CM4 in the IEEE802.15.4a channel model is analyzed through simulation, simulation on static nodes and dynamic users in indoors is performed, which verifies the validity and reliability of the dual-state Kalman filter algorithm and can be applied in medical field for patients tracking in real time and so on.

Airborne Single Observer Passive Location has the characteristics of mobility and a wide range impaction, while location method basing on phase difference change rate also has the characteristics of getting a quick location with high precision. Studying the Kalman Filter (KF) applied in Airborne Single Observer Passive Location, it analyzes the principle of the position method basing on phase difference change rate, and introduces the filtering principle and the filtering process of the KF algorithm. The simulation results show that, KF algorithm used in Airborne Single Observer Passive Location has an accurately positioning and rapid convergence.

In single observer passive location system, traditional filtering algorithm for nonlinear system is Extended Kalman Filtering (EKF), which is usually affected by initial values and measurement noise of passive tracking. In order to overcome the disadvantages of EKF, we present an improved Modified Variance Extended Kalman Filter (MVEKF) method in single observer passive location system, using phase difference rate. Simulation results show that it can effectively restrict the measurement noise, being less affected by initial values. Furthermore, there is no need for searching observables modifiable function, so the proposed MVEKF is more accurate and useful than EKF in single observer passive location.

With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. GA and chaos optimizing was integrated, by use of the chaos serial's property of "ergodicity, randomicity, regularity" to generate original population; adding chaotic fine search to genetic operation greatly improves the local search ability, which avoids local optimization and premature convergence in effect. The results of the simulation demonstrate that the chaos genetic algorithm has ideal and satisfied optimization result and much better than that of common genetic algorithm.