A study on a support of decision-making for collision avoidance in INS

In order to satisfy the demand for highly automated and fully safe ship operation, it is desirable that an Integrated Navigation System (INS) has an intelligent decision-making supporting function. Such a function can propose a proper maneuvering action to operators. Of course, the operators should decide a final action by their judgment supported by other available supporting functions of the INS. To implement such a supporting function, the authors have developed a collision avoidance expert system for such the INS. In this paper, the structure of developed knowledge bases, the inference procedure, the brush-up of the developed knowledge bases using ship handling simulator, and some simulation results are reported. Some concepts and methods concerned to this knowledge base system, such as the classification of the target ships, the unblocking scope of the ship handling space and the prediction of plural actions of target ships, are proposed. The conclusion is that the developed collision avoidance expert system possesses sophisticated problem solving ability for the collision avoidance and it can provide an effective support for operators' decision-making.

A new integrated navigation system designed for small size Unmanned Aerial Vehicles (UAVs) is presented. The proposed system is based on a number of low-cost avionics sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Sensors (VBS). The use of an Aircraft Dynamics Models (ADMs) to provide additional information to compensate for the shortcomings of Vision Based Navigation (VBN) and MEMS-IMU sensors in high-dynamics attitude determination tasks is also considered. Additionally, the research concentrates on the potential of carrier-phase GNSS for Attitude Determination (GAD) using interferometric techniques. The main objective is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance (position and attitude data) in all phases of flight of small UAVs, with a special focus on precision approach and landing, where VBN techniques can be fully exploited in a multi-sensor data fusion architecture. An Extended Kalman Filter (EKF) is developed to integrate the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UAV platform in real-time. Three different integrated navigation system architectures are implemented. The first architecture uses VBN at 20 Hz and GNSS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. The third fusion architecture uses GNSS based attitude values. The simulations are carried out on the AEROSONDE UAV performing high-dynamics manoeuvres repre-sentative of the UAV operational flight envelope. Simulation of the VBN-IMU-GNSS (VIG) integrated navigation system shows that the system can attain position, velocity and attitude accuracies complying with Category Two (CAT II) precision approach requirements. Simulation of the VBN-IMU-GNSS-ADM (VIGA) system also shows promising results, since the achieved attitude accuracy is higher using the ADM-VBN-IMU than using VBN-IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed. In the simulation of the third integrated navigation system, the VIG system is augmented by employing the GAD, forming the VIG-GAD (VIGGA) system architecture. The performances achieved with the VIG, VIGA and VIGGA integrated Navigation and Guidance System (NGS) are presented and are in line with the International Civil Aviation Organization (ICAO) precision approach requirements.

Ship-handling simulator is often used to train seamen for maneuvering andlor to research marine environments and so on. Lacking the validation for the simulator's function, it is so often that the construction of very expensively large shiphandling simulator is adopted in order to pursue the reality of simulation too. In this reason authors studied the validation of shiphandling simulator's function by clming the role that the simulator's function contributes for using simulators in which typical nautical missions are executed under maneuvering situations such as Collision avoidance, Passing fairway, Approaching anchorage and Berthing. The result of this study showed the relationship between the ship-handling simulator's functions and shipoperator's performance corresponding nautical missions were discussed with the results of experience using the Full Mission Simulators in Japan to validate the simulator's function. In this paper, the relationship between simulator's function and human performance are presented after complements of study and

This paper presents a viable approach for incorporating collision avoidance strategies into existing guidance and control systems on marine vessels. We propose a method that facilitates the use of simulation-based Model Predictive Control (MPC) for collision avoidance (COLAV) on marine vessels. Any COLAV strategy to be applied in real traffic must adhere to the international regulations for preventing collisions at sea (COLREGS). The proposed MPC COLAV method does not rely on an accurate model of the guidance system to achieve vessel behaviors that are compliant with the COLREGS. Rather, it depends on transitional costs in the MPC objective for collision avoidance maneuvers that are being executed by the marine vessel. Hence, it is straightforward to implement the MPC COLAV on different vessels without specific knowledge of the vessel's guidance strategy. Moreover, it offers the possibility to switch between different (possibly application specific) guidance strategies on the same vessel while running the same MPC COLAV algorithm. We present results from full scale experiments that show the viability of our method in different collision avoidance scenarios.

As part of our recent research to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicle (UAV) applications, we investigated the potential of carrier-phase Global Navigation Satellite System (GNSS) for attitude determination and control of small size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro- Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD)sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

During the process of collision avoidance, especially in a multi-ship encounter situation, the dynamic interactions among individual ships impose a significant impact on collision avoidance decision-making. It is imperative, therefore, that collision avoidance decisions are formulated with a comprehensive consideration of not only the current direct collision conflict but also the potential conflicts due to planned collision avoidance actions. To address this requirement, this paper proposes a dynamic conflict cluster detection method for collision avoidance decision-making in multi-ship encounters. The involved ships are clustered into stable temporal-dependent ship conflict groups taking into account both conflict connectivity and the potential spatiotemporal interactions originating from planned collision avoidance actions. The conflict cluster detection model is implemented within a framework to achieve hierarchical coordinated collision avoidance decision-making. By a simulation experiment of an 11-ship encounter, the proposed method successfully discerns the ships with conflicts and provides feasible collision avoidance decisions. Compared to the non-cluster collision avoidance methods, the proposed method generates the results with acceptable deviating distance and number of collision avoidance actions at minimum computation load. It has been demonstrated that the proposed method is both effective and efficient for officers on board and operators at Vessel Traffic Services centers in real-life navigation.

This paper presents a new approach for integrated landing systems. Applicable avionics platforms are military aircraft, helicopters, and unmanned aerial vehicles. In this paper we focus on the introduction of NILS (new integrated landing system) in the Saab fourth generation fighter JAS39 Gripen. NILS is based on an integrated navigation system (NINS) which is covered in the paper as well. The landing system in older generations of aircraft is usually designed by combination of different equipment. In the fourth generation aircraft the same functionality is solved in software implemented in the aircraft system computers. Typical applications of Saab NINS are accurate random route navigation (RNAV) under instrument flight rules, inputs to the auto-pilot, ground collision avoidance system (GCAS), terrain following, landing system and weapon initialization. Future applications are inputs to head-up or head-down display synthetic terrain presentation, mid-air collision avoidance system (MCAS) and passive target ranging.

In this paper, two new methods are developed to improve the sensitivity of the failure detection system, where the chi-square test is used to monitor the state estimates of the Kalman filter: (1) Using two state propagators, which are reset regularly with the data of the Kalman filter to increase their accuracy and so the detection sensitivity of the system, and used as the failure detection reference alternatively to avoid the risk of using the contaminated state propagator as the reference system for failure detection. (2) Monitoring the state estimates of the Kalman filter individually, so that the test statistics most seriously affected by the failures are utilized to enhance detection sensitivity. The effectiveness of the proposed approaches is demonstrated in the failure detection problem of a SDINS(Strapdown Inertial Navigation System)/GPS(Global Positioning System) integrated navigation system. The simulation results show that the failure sensitivity is remarkably increased. The system functions quite well to detect the soft failures in the gyros and accelerometers.

Uninhabited Aerial Vehicles will require autonomous collisio n detection and avoidance capabilities in order to gain wide acceptance and usage in the National Airspace System. The collision detection and avoidance problem is primarily a motion estimation problem, relying on the accuracy of the sensing, processing, actuation and control algorithms onboard the vehicle. Computer vision is a growing field in robotics and autonomous vehicles, and has made vision a feasible technology for object detection in different platforms. In this work, we investigate the feasibil ity of using optic flow techniques in order to design an altitude hold controller for a fixed wing aircraft flying a nap -of -the -earth trajectory in the presence of variable terrain. Simulated results yield an error of approximately 1.5% in altitude variat ion for steady level flight (approximately 15 cm) for terrain disturbances of maximum amplitude 4 m. Experimental results obtained from flight data using the UIUC UAV platform are used to validate the controller, and sources of error along with potential improvements in equipment and procedures are cited. I. Introduction N essential challenge inherent to the integration of uninhabited aerial vehicles (UAVs) into the National Airspace System (NAS) is the inability to provide adequate safety assurances for th ese vehicles in a verifiable manner. The FAA requires that UAVs be capable of see -and -avoid functionality, unfortunately most solutions to the problem of autonomous surveillance, guidance and navigation are insufficiently scalable, reliable, verifiable or cost -effective. Implementation of safe and reliable object avoidance is crucial for the survival of autonomous vehicles intended to navigate in densely populated environments such as the NAS. In order to meet these stringent requirements, UAVs must be eq uipped with reactive sensing technologies that enable real -time conflict detection and object avoidance. Numerous techniques have been developed in the past few years to optimize the decision making process and solve the path planning problem in real -time , while accounting for aircraft dynamics, obstacle avoidance constraints and safe flight considerations. Regrettably, many of these techniques underestimate the difficulty of accurately sensing a dynamic and imperfect environment in an accurate and practic al manner. Making decisions based on distorted estimations of the surrounding environs is a pitfall that can destabilize even the most robust of path planning algorithms. Presently, state -of -the -art conflict detection and resolution systems employ a combi nation of radar, sonar and laser systems: while reliable, these systems are often prohibitive due to weight, size and equipment cost for certain UAV applications. Video recording devices are another alternative for environmental sensing, and have become standard equipment on many UAVs due to their exploratory nature. Although video images from this source are often intended for secondary mission purposes, such as target tracking and surveillance, they have been shown capable of providing valuable informati on for more important tasks, like collision avoidance. However, the nature of a fixed wing UAV platform brings rigorous safety requirements and constraints to the field of autonomous conflict detection and resolution: limited minimum flying speeds and res tricted maneuverability, thereby making the need for real -time sensing and decision -making paramount for safety purposes. In this paper we investigate the applicability of c omputer vision techniques that have been developed in order to estimate motion from two dimensional images. In the next section we provide a brief discussion of optical flow theory, and section 3 provides a direct implementation of the optical flow theory to an aircraft altitude controlle r. Section 4 provides the setup and simulation of several scenarios used to evaluate the performance of the controller designed in the previous section. Experimental video data taken from actual flight tests is used in order to asses the 1

Operations in the Next Generation Air Transportation System (NextGen) are planned to have a reduced dependency on primary surveillance radar and use Automatic Dependent Surveillance - Broadcast (ADS-B) to provide aircraft state information to Air Traffic Control (ATC) and onboard collision detection and avoidance systems. With the ongoing integration of Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS), ADS-B is expected to become the main surveillance input to UAS collision avoidance. Traffic Alert and Collision Avoidance System (TCAS) is unable to meet requirements in terms of adaptability to future operations with reduced separation margins, addition of new user groups (e.g., UAS), and support of additional surveillance inputs. Airborne Collision Avoidance System (ACAS X) is being designed to meet these requirements and to increase surveillance, alerting, and resolution performance. The RTCA has released Minimum Operational Performance Standards (MOPS) to provide system and operational performance characteristics that ADS-B must provide. This paper analyzes recorded ADS-B data from test flights that were performed in the Continental U.S. (CONUS) and verifies measured performance with specified operational characteristics in terms of coverage, accuracy, and integrity.

NASA and the U.S. Army have designed, developed, and flight evaluated a Computer Aiding for Low Altitude Helicopter Flight (CALAHF) guidance system. This system provides guidance to the pilot for near terrain covert helicopter operations. It automates the processing of precision navigation information, helicopter mission requirements, and terrain flight guidance. The automation is presented to the pilot through symbology on a helmet-mounted display. The symbology is a 'pilot-centered' design which preserves pilot flexibility and authority over the CALAHF system's automation. An extensive flight evaluation of the system has been conducted using the U.S. Army's NUH-60 STAR (Systems Testbed for Avionics Research) research helicopter. The evaluations were flown over a multiwaypoint helicopter mission in rugged mountainous terrain, at terrain clearance altitudes from 300 to 125 ft and airspeeds from 40 to 110 knots. The results of these evaluations showed that the pilots could precisely follow the automation symbology while maintaining a high degree of situational awareness.

Aiming at the fact that target ships of ship handling simulator have not the ability of avoiding other ships according to the COLREG 1972, the paper puts forward to add Personifying Intelligent Decision-making for Vessel Collision Avoidance, for short PIDVCA, and vessel automatic control algorithm into solver procedure of target ship, designed and realized target ships to sail according to the COLREG 1972, which make ship handling simulator more realistic simulate the actual navigation environment at sea. Finally, the paper gives the simulation pictures of 2 and 4 target ships intelligent collision.

COLREGs-abiding hybrid collision avoidance algorithm based on deep reinforcement learning for USVs

Global Positioning System (GPS) spoofing is a common mean to cheat an Unmanned Aerial Vehicle (UAV) which is guided by the INS/GPS integrated navigation system. Detecting the spurious GPS signal is the precondition of anti-spoofing for UAVs. A detection system of GPS spoofing is designed based on dynamics identification. The centroid motion model and attitude motion model were established. The measurement information from inertial measurement units (IMUs) and positioning information from GPS both are visualized responses to the dynamic laws of UAVs. These two types of measurement information were separately used to estimate the dynamics parameters of UAVs online using two Extended Kalman Filters (EKFs). The detection of spurious GPS signals was realized effectively based on the monitoring of relative estimation errors. Numerical simulations demonstrated that the dynamics parameters could be estimated online by the combined filters. And the precision and accuracy of filter #1, which was based on IMU information, were both higher than those of filter #2, which was based on GPS information. When the spurious GPS signal was just zero-order continuous with the true signal at the penetration point, a pulse relative error would occur at the penetration point; when the spurious GPS signal was first-order continuous with the true signal at the penetration point, a step relative error would occur. Furthermore, relative systematic errors matched with the period of spurious signals.

The integrated system for the measurement of movement parameters, constructed on the basis of a tightly coupled scheme of integration of inertial and satellite navigation systems is considered in the paper. The main objective is the improvement of the measurement accuracy of navigation information and ensuring the measurement of movement parameters in conditions when each separate system does not provide sufficient accuracy for practical tasks. The applied algorithm for recursive estimation of errors of resultant integrated navigation system allows real-time correction of indicators of inertialand satellite navigation systems, that leads to the increase of the measurement accuracy of navigation parameters.This paper shows the dependence of the achieved effect of the increased accuracy on the nature of movement, arrangement and number of satellites, and also trajectory orientation relative to the satellites, signals from which enter the receiver of satellite navigation system. The proposed algorithm can be used in the aviation industry, in guidance and flight control systems, and also onboard information-measuring systems of aircrafts, operating in the presence of radio frequency interference.