Real-time Navigation Information Research Articles

Autonomous UAV Safety Oriented Situation Monitoring and Evaluation System

In this paper, a LabVIEW-based online monitoring and safety evaluation system for UAVs is designed to address the deficiencies in UAV flight state parameter monitoring and safety evaluation. The system consists of a lower unit for UAV recording and an upper unit on the ground. The lower unit collects and detects flight data and connects to the upper unit through a wireless digital transmission module via a serial port. The upper unit receives the data and carries out the monitoring and safety situation evaluation of the UAV. The lower unit of the system adopts multi-sensors to collect UAV navigation information in real time to achieve flight detection, while the upper unit adopts LabVIEW to design the UAV online monitoring and safety situation prediction system, enabling monitoring and safety situation prediction during UAV navigation. The test results show that the system can detect and comprehensively display the navigation information of the UAV in real time, and realize the safety evaluation and warning function of the UAV.

An Indoor Real-Time Visualization Exploration Unmanned Aerial Vehicle

Aiming at the scene of a rescue in an indoor environment, this paper proposes an indoor real-time visual exploration UAV. UAVs can model the unknown space in 3D space in real-time, obtain obstacle information and flight navigation information, avoid obstacles and fly to the region of interest in real-time. Real-time transmission of three-dimensional space information to the remote end to provide rescue personnel with timely arrangements for rescue plans. The 3D mapping uses a 32-line laser radar, combining high-density point clouds and IMU to obtain accurate and real-time navigation information. The point cloud is then made into a grid map for real-time planning so that the UAV can independently calculate the flight path to the designated area. Then it is transmitted to the remote interface in real-time through WIFI communication so that the rescuers can quickly get the location and route of the rescuers needed and complete the rapid rescue operation.

Vision-based environment perception and autonomous obstacle avoidance for unmanned underwater vehicle

We propose two schemes to solve the problems of visual perception delay and limited obstacle avoidance capability in the autonomous navigation of unmanned underwater vehicles (UUV). In the aspect of visual perception, this paper presents a compressed algorithm based on the UNDERWATER-CUT model for underwater image enhancement and a two-stage compressed YOLOv5s model for object detection, simultaneously reducing the model volume, decreasing the run-time memory footprint, and lowering the number of computing operations, without compromising enhancement effect and recognition accuracy. The 2D coordinates of the obstacles acquired by the visual perception algorithms and the depth values by the depth camera are then merged into real-time navigation information. In terms of obstacle avoidance, this paper proposes the adapted modified guidance vector field (AMGVF) to achieve autonomous navigation. A high-fidelity underwater simulation platform based on AirSim is constructed to jointly validate the above algorithms. Finally, the experimental results on visual perception and obstacle avoidance show that the above methods apply to the UUV well in complex underwater environment.

Raspberry Pi-based Virtual Reality Headset for Cyclist Services

Following the development of technology and people's pursuit of a better life, MR technology has been applied in more and more scenarios. Based on the current research status, this project proposes to design a MR headset for cyclists. The helmet is developed based on Raspberry Pi, equipped with heat dissipation function, HD camera, and infrared camera are selected as sensing devices, HD camera is enabled in good light conditions, and the infrared camera is enabled in bad light conditions. The rider can observe the road conditions and outside information through the camera displayed in MR glasses in real-time. In addition to the live camera screen display, it can also display the time, memo information, and other functions. The map screen can be called up to show real-time navigation information. In addition, the helmet has built-in small Bluetooth audio. It can be connected to the phone via Bluetooth. The helmet is equipped with a total of three high-brightness LED light strips installed on the front and rear side of the helmet, which can be controlled by a button to make the light strip achieve the function of the turn signal. The gyroscope is installed in the button box of the light belt control. After detecting a fall, the buzzer and LED lights will go into alarm mode, which can improve the safety of the user's ride.

Certificateless Aggregate Signature Scheme with Conditional Privacy Protection in Vehicle Networking

Real-time road navigation information update in vehicle networking plays an extremely important role in safe driving and alleviating traffic congestion, but how to protect user privacy from leakage is a major challenge when updating real-time navigation information. In order to solve this problem effectively, a certificateless aggregate signature scheme with real-time navigation information update function is proposed, which is suitable for vehicle networking. In the scheme, when the navigation company needs to access the data, the fog node aggregates the signature message of the vehicle broadcast and uploads it to the trusted center, and then feeds it back to the navigation company after batch verification by the trusted center. The trusted center generates temporary pseudonyms for vehicle users, realizes the anonymity of user identity, and meets the requirements of conditional privacy protection. The aggregate signature technology is used to reduce the computing and communication overhead. Finally, based on the discrete logarithm difficulty problem in the elliptic curve, it is proved that the scheme satisfies the existence and can not be forged under the adaptive selection message attack. The results of numerical analysis show that the scheme has some advantages in terms of computational cost.

Improved GPS/IMU Loosely Coupled Integration Scheme Using Two Kalman Filter-based Cascaded Stages

Despite the fact that accelerometers and gyroscopes are used in inertial navigation systems (INS) to provide navigation information without the aid of external references, accumulated systematic errors are shown in sensor readings on long-term usage. In this work, a new approach is proposed to overcome this problem, by using extended Kalman filter (EKF)—linear Kalman filter (LKF), in a cascaded form, to couple the GPS with INS. GPS raw data are fused with noisy Euler angles coming from the inertial measurement unit (IMU) readings, in order to produce more consistent and accurate real-time navigation information. The proposed algorithm is designed to run through three software threads simultaneously. The multi-thread processing provides better use of hardware resources and applies more efficient INS/GPS loosely coupled integration scheme compared to the conventional method. Two datasets are used to verify the efficacy of the proposed approach against the existing GPS/INS coupling techniques. The first set is synthetic data generated by MATLAB that represents a static vehicle at known coordinates. The second one is a real road test data collected in Ontario, Canada. Accordingly, the root mean square error (RMSE) values for the proposed approach in ENU directions have reached 0.022, 0.034 and 0.010 m, respectively, for a static vehicle, as well as 0.493, 0.453 and 0.110 m, respectively, for a movable vehicle—which is notably competitive with other recent related work.

Inference Model of Collision Risk Index based on Artificial Neural Network using Ship Near-Collision Data

The judgement of Collision Risk Index (CRI) is important for safe navigation. The autonomous ship need to analyze and decide taking an action for collision avoidance. Recently, it has been possible of navigator to obtain navigation information in real time. By using such collected navigation information, many researchers have proposed inference models which are based on the fuzzy theory in order that they can make decision for safety of navigation. The conventional inference model, however, have several limitations: (i) establish a membership function with Distance of the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) without any considerations for other ship dynamic parameters; and (ii) rely on values of simulation result using virtual navigation information. In order to overcome these limitations, we introduces the inference model with Artificial Neural Network (ANN) by learning input vector, i.e., own ship’s speed, target ship’s speed, own ship’s course, target ship’s course, bearing between own ship and target ship, distance between own ship and target ship, and target vector. Taking an actual near-collision situation into account, the proposed model can express various CRI, keeping the desirable TCPA and distance to take a proper action for collision avoidance. The proposed method conducts better decision-making than conventional ones.

An INS/Geomagnetic Integrated Navigation Algorithm Based on Matching Strategy and Hierarchical Filtering

To improve the positioning accuracy of an inertial/geomagnetic integrated navigation algorithm, a combined navigation method based on matching strategy and hierarchical filtering is proposed. First, the PDA-ICCP geomagnetic matching algorithm is improved. On basis of evaluating the distribution of magnetic measurements, a number of controllable magnetic values are regenerated to participate in the geomagnetic matching algorithm (GMA). As a result, accuracy of the matching algorithm is ensured and its efficiency is improved. Secondly, the integrated navigation filter is designed based on the hierarchical filtering strategy, in which the navigation information of the geomagnetic matching module and inertial navigation module are respectively filtered and fused in the main filter. In this way, the shortcoming that GMA is unable to provide continuous and real-time navigation information is overcome. Meanwhile, precision of the inertial/geomagnetic integrated navigation algorithm is improved. Finally, the feasibility and validity of the proposed algorithm are verified by simulation and physical experiments. Compared with the integrated filtering algorithm which directly uses the error equation of inertial navigation system (INS) as the state equation, the proposed hierarchical filtering algorithm can achieve higher positioning precision.

Multi-target collision avoidance route planning under an ECDIS framework

The universality of the automatic identification system (AIS) as well as the electronic chart display and information system (ECDIS) installations will provide revolutionary solution schemes for the e-navigation era of informatization, intellectualization, and integration. Based on this concept, this study adopted ECDIS as an information platform for navigational decision support and used the real-time navigation information received by the AIS to construct predicted areas of danger (PAD) for target ships. The advantages of direct viewing via the PAD in the collision avoidance give PAD a new application. Subsequently, spatial data from an electronic navigation chart (ENC) was employed as a basis for generating geographical obstacles. Through the integration of a geographic information system (GIS) module, specially designed evolutionary computation, and collision prevention regulations (COLREGS) knowledge as well as by comprehensively considering overall navigation situations, this system conducted obstacle avoidance processing and selection of a route. The system could generate a route that could simultaneously achieve multi-ship encounter collision avoidance and geographical obstacle avoidance. This is expected to provide mariners with greater convenience when working at sea, reducing their workload. This system can also be used as a reference for collision avoidance decision making.

X-ray pulsar/starlight Doppler integrated navigation for formation flight with ephemerides errors

Currently, the deep space explorer formation fight is a novel area of aerospace technique [15]. The formation fight can increase redundancy backup, decentralize the cost, and provide a multi-platform for the deep space exploration [17]. For the deep space explorer formation fight, both absolute and relative navigation accuracies are crucial, especially the relative one. Orbit determination of a spacecraft is primarily performed at a ground station [4]. Unfortunately, subject to the long distance between the explorer and the earth, traditional ground station-based navigation methods cannot provide high-accuracy and real-time navigation information. Consequently, the autonomous navigation systems [12], [13], which observe the celestial bodies to obtain the navigation information, are highly attractive.

The Optimal Traffic Information Process System by Using MIMO Algorithm

This paper presented dynamic vehicle information for wireless communication and safe systems by integrating radio frequency identification (RFID) technology. The systems provied different particular and advantage between RFID and other recognition technology. The car black box is the best choice and innovates specific application. It is not only the system can guard car but differentiate the responsibility for car accident event. Furthermore, the car black box is integrated the RFID, general packet radio service (GPRS), Bluetooth, personal digital assistant (PDA) and global positioning system (GPS). The proposed system has been trending the merger goal of digitization. Therefore, it is created a tremendous amount of commercial opportunity. The car black box is also combined multiple-user with real-time navigation information system. The system is integrated the independent real-time traffic information database and Geographical Information System (GIS) through data fusion method. We adopted a traffic information system offering advanced personalized route planning, including added services for traffic jam alerting by means of Short Message Service (SMS) in Global System for Mobile (GSM) communication network. It is shown small and low-cost GSM modules for data process by using the Multiple Input Multiple Output (MIMO), Ant colony optimization (ACO) algorithm, which developed a real-time software solution to help users and evaluation of user preferences for car traffic information system.

중첩모델 기반 레이저 관성항법장치 고장검출 기법

LINS (Laser Inertial Navigation System) consists of RLG (Ring Laser Gyroscopes)/accelerometers and provides real-time navigation information to the target system. Therefore it is very important to make a decision in the real time whether LINS is in the normal operation or not. That is called a fault detection method. In this paper, we propose the fault detection method of LINS based on the overlapping model. We also show that the fault detection probability is increased through overlapping the hardware model and the software model. It is verified through the long-term operation and RAM (Reliability Availability Maintainability) analysis of LINS that the fault detection method proposed in this paper is able to detect about 97% of probable system failures.

THE STUDY OF SHIP COLLISION AVOIDANCE ROUTE PLANNING BY ANT COLONY ALGORITHM

Maritime traffic is becoming more complex every day. At present, due to technological advances and to new maritime regulations, there is increasing demand for new nautical marine instruments to be installed into the bridge, and the breadth of navigational information complicates on-duty officers' decisions. Therefore, if decision support tools can be used to help deal with navigational decision-making, human errors arising from subjective judgments can be reduced, and sea transport safety improved. This research uses the concept of e-navigation as a framework, positioning collision avoidance path planning as the main theme, and applies an Ant Colony Algorithm (ACA) in the field of artificial intelligence to construct a collision avoidance model that imitates optimization behaviors in real-life applications. This model combines navigational practices, a maritime laws/regulations knowledge base and real-time navigation information from the AIS to plan a safe and economical collision avoidance path. Through using such planning, recommendations can be made for collision avoidance and return to course. Lastly, a Geographic Information System (GIS) was used as the platform for a navigation decision support system, combining related navigation information, collision avoidance models and electronic charts. This is a source of reference for VTS (Vessel Traffic Service) operators and on-duty officers to assess collisions in territorial waters, achieving objectives such as warning and pre-collision preparations.

A Localization and In-flight Alignment Protocol for Airborne SINS Based on Flight-vehicle Wireless Sensor Networks

The necessity recurrently comes to align a strapdown inertial navigation system (SINS) in a moving vehicle to guarantee the accuracy and efficiency in the long run-off of the inertial system after a take-off or launch command is issued. This in-flight alignment is therefore achieved by integrating SINS data with some external aiding source inlcluding airborne navigation equipments and networking sensors. In this paper, a localization architecture and alignment scheme is presented for aircraft in a three-demensional fleet network, which is based on wireless sensor network. Firstly, a 3D node localization scheme is designed based on weighed-multidimensional scaling, which adopt spherical locating in the initial stage, and adaptively choose source nodes with high relative reliability to achieve position update. Then a robust filter algorithm is applied to compensate time-varying delay error and large azimuth uncertainty in alignment. Extensive simulation shows that the DMDG-3D localization scheme can provide highly accurate and relatively reliable navigation information in real time, and filter algorithm can accelerate convergence and give better estimation of the navigation parameters. ∞ − l l2

A method for bronchoscope tracking by combining a position sensor and image registration

This paper describes a method for tracking a bronchoscope by combining a position sensor and image registration. A bronchoscopy guidance system is a tool for providing real-time navigation information acquired from pre-operative CT images to a physician during a bronchoscopic examination. In this system, one of the fundamental functions is tracking a bronchoscope's camera motion. Recently, a very small electromagnetic position sensor has become available. It is possible to insert this sensor into a bronchoscope's working channel to obtain the bronchoscope's camera motion. However, the accuracy of its output is inadequate for bronchoscope tracking. The proposed combination of the sensor and image registration between real and virtual bronchoscopic images derived from CT images is quite useful for improving tracking accuracy. Furthermore, this combination has enabled us to achieve a real-time bronchoscope guidance system. We performed evaluation experiments for the proposed method using a rubber phantom model. The experimental results showed that the proposed system allowed the bronchoscope's camera motion to be tracked at 2.5 frames per second.

The Electronic Chart

The Canadian Hydrographic Service began its involvement in collecting and processing digital hydrographic data in the late 1960s. During the intervening years the Service has been actively involved in the development, testing and implementation of digital data acquisition systems for the recording and processing of hydrographic data and the processing of digital data in the chart production process. So far the orientation of the overall process has remained toward the eventual production of the conventional nautical chart. The value of the digital data itself for the maintenance of the charts and possibly its eventual use on the bridge was of course recognized. Today the technological push is toward the increase of microprocessor technology in the instrumentation packages. Electronic positioning systems facilitate computer processing for real-time navigation information. Display technology, particularly video displays now make possible the graphic presentation of data stored within a digital database. Coincidentally marine traffic is increasing and the costs of marine disasters are escalating. Therefore it is reasonable to assume that there will be a demand to integrate positioning and collision avoidance radars with navigational information contained on the nautical chart. This paper will review this technology and consider the future role of information contained on the nautical chart as it will be used in the electronic systems on the bridge.