연근해 어선 통합항법시스템의 구축

국제해사기구(International Maritime Organization, IMO)에서는 선박의 해상 충돌을 방지하기 위하여 SOLAS의 요구조건에 따라 모든 선박에 대하여 선박자동식별장치(Automatic Identification System, AIS)를 의무적으로 장착하도록 권고하고 있다. AIS를 사용하면 타선에 대한 제원 및 항행정보의 획득이 가능하여 충돌방지뿐만 아니라 광역관제, 조난 선박의 탐색구조 등 안전관리에도 활용이 가능하다. 본 논문에서는 AIS 장비를 사용하여 ADS-B (Automatic Dependent Surveillance - Broadcast) 개념 기반의 항공감시용 송수신기를 구현한 결과에 대하여 살펴보도록 한다. 기본적으로 AIS는 해상에서 사용되기 때문에 고도 정보를 사용하지 않지만, AIS 장비 내부에 사용하는 GPS (Global Positioning System) 칩셋에서 제공하는 고도 정보의 추출이 가능하다. 고도 정보를 포함한 감시 메시지 형식을 정의하고, SOTDMA (Self-Organizing Time Division Multiple Access) 방식을 개선하여 ADS-B 송수신기를 구현하였다. 적용 결과를 확인하기 위하여 지상시험 및 비행시험을 수행하였다. International Maritime Organization (IMO) recommends the installation of an Automatic Identification System (AIS) according to requirements by SOLAS to avoid maritime collision. AIS provides traffic information of other ships that may be used for maritime traffic control, SAR (Search and Rescue) and collision avoidance to apply safety management. In this paper, preliminary results to implement an aeronautical surveillance transceiver using AIS transceiver based on ADS-B concepts are described. Although altitude information is not required for AIS since the AIS is operated at MSL (Mean Sea Level), altitude information can be extracted by a GPS (Global Positioning System) chip-set in the AIS transceiver. ADS-B transceiver is implemented by defining a surveillance message format including the altitude information and modifying SOTDMA (Self-Organizing Time Division Multiple Access) protocol. Ground tests and flight tests are performed to validate the implementation results.

How to achieve continuous, reliable and accurate positioning performance using low-cost sensors is one of the main challenges for aviation navigation system. Global Positioning System (GPS) can provide the primary means of navigation in a number of aviation navigation applications (e.g., manned and unmanned aircraft vehicle, airport ground vehicle). However, GPS signal deteriorations typically occur due to aircraft itself during maneuvering, ionospheric scintillation, Doppler shift, multipath and so on. Thus, there is a need to research GPS augmentation strategies which can be used in the Communication, Navigation, Surveillance/Air Traffic Management. GPS integration with Inertial Navigation system (INS) is one of the key strategies. But once GPS signal outages, the integrated navigation system works in pure INS, and positioning accuracy deteriorates with time. When using low cost GPS/INS integration, a primary problem is the rapid performance deteriorate during GPS outages. To provide continuous, accurate and reliable positioning information in aviation, discrete grey prediction model (DGPM) aided fusion methodology is proposed. The DGPM provides pseudo-GPS position information for INS during GPS outages. The mathematical model of integrated navigation system is established, including INS error equations, Kalman filter and DGPM. The model works in the update mode when there is no GPS failure, whereas it switches to the prediction mode in case of GPS outages. To verify the feasibility and effectiveness of the proposed methodology, real road test is performed. The comparison results show that accuracy of longitude and latitude are improved by more than 80% and 70%, respectively. The DGPM can effectively provide position corrections for standalone INS during GPS outages.

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.

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) are very practical method to get high precision navigation. GPS/INS data Fusion in navigation has been a research topic for decades. Usually the update time of GPS an INS is different. The update time of GPS is 20HZ, and the time of INS is 100HZ or higher. Since GPS and INS are mainly methods in navigation system. Techniques of fusing GPS and INS data are in high demand in navigation industry. Usually the Karman filter is used to fuse the data from GPS and INS. But the Kalman filter is model-dependent and a priori the model parameters need to be known. In this work, a generic and intelligent approach of GPS and INS data fuse using fuzzy interpolation before Kalman algorithm is proposed. First a simplified interpolation model is introduced in a ordinary GPS and INS data fusion. Second a fuzzy rule-based system is established to fuzzy interpolation with objective fuzzy method. Then the parameters of objective fuzzy system are identified, the best n-rule is determinate and the optimal rule base system is found. Finally this approach is applied on an example for a car GPS and INS data fusion, and the results are calculated with computer system to demonstrate the advantages of this approach.

Abstract. High accuracy positioning is crucial for various applications that require accurate and reliable positioning data, such as autonomous vehicles (AVs), agriculture, and intelligent transportation. Global Positioning System (GPS) is widely used in integration with Inertial Measurement Unit (IMU) and Visual Odometry (VO) to implement an accurate and robust navigation system. However, the performance of the integrated system can be severely degraded in urban environments due to non-line-of-sight (NLOS) reception and multipath interference. To overcome these challenges, a novel Fault Detection and Exclusion (FDE) algorithm aided with IMU and VO measurements is proposed to identify and isolate the contaminated satellite signals. The algorithm utilizes instantaneous measurements from IMU and VO to predict the current vehicle position, enabling the estimation of pseudorange errors in GPS measurements. A FDE algorithm based on Hierarchical clustering is then developed to identify GPS signals with significant errors based on the predicted pseudorange error. An experimental field test was conducted using a land vehicle to evaluate the effectiveness of the proposed algorithm. The results show that the GPS/IMU/VO integrated navigation system with the proposed FDE algorithm has significantly improved the positioning accuracy and reliability compared to the traditional system. The proposed algorithm achieves a positioning accuracy with a 3D Root Mean Square Error (RMSE) of 11.18m in urban environment, making an improvement of 68.2% over the traditional GPS/IMU/VO integrated navigation system.

When designing the Kalman filter of integrated navigation system, the point of pinnacle importance focuses on the systemic state equation and measurement equation. Aiming at the relativity and poor observability among measurement information in loosely coupled integrated navigation system, the tightly coupled integrated navigation system is constructed with the information fusion technology based on Kalman filter. In this mode, pseudo-range and pseudo-range rate are used as measurement information for their better observability and independence, to improve the accuracy of Kalman filter. The experiments are carried out based on semi-physical, using the actual datum which are received by Global Position System (GPS) software receiver. The results show clearly that when the accuracy of inertial components declines, the tightly coupled integration can provide higher position accuracy than the loosely coupled integration.

For the guidance, control and navigation of autonomous vehicles, both positioning and orientation are important for mission success and surveillance. Global positioning system (GPS) and strapdown inertial navigation system (SINS) have complementary characteristics to overcome the demerits of each other and can well perform as integrated navigation system. The observability analysis of low-cost SINS/GPS from many researches shown that the heading and yaw rate gyro bias is unobservable in straight motion and with constant acceleration. This paper presents integration of low-cost SINS/GPS aided with odometer and heading from two antennae GPS receiver to overcome this problem and to control the accuracy degradation during GPS outage. The carrier phase measurements are processed to obtain the heading from two antennae position measurement. The obtained heading and position from GPS and velocity measurement from odometer are used as observation input to extended Kalman filter (EKF) for the heading and positioning accuracy improvement of SINS/odometer/GPS integrated system for land vehicle navigation. When GPS signal is unavailable, the filter switches to SINS/odometer integration to control the position and velocity errors growth during this period. The observation model for heading measurement from two antennae is derived for the designed system. A field test was conducted to check the effectiveness using proposed method for heading and positioning accuracy improvement. The test results showed that Low-cost IMU/Odometer/ Two Antennae GPS integrated systems' accuracy both in position and heading is improved significantly.

The Global Navigation Satellite Systems (GNSS) such as Global Positioning System (GPS) are the prime land and autonomous vehicles navigation information source. However, urban canyons high rise buildings block the GPS signal. Therefore, the Inertial Navigation System (INS) or the Reduced Inertial Sensor System (RISS) are utilized as an alternative source of the navigation information. The RISS is able to produce a full navigation solution using less number of sensors and calculations. Dramatically, the RISS solution drifts over time as the INS system. The integration between the GPS and the RISS is mitigating each system drawbacks. However, during the GPS outage periods, the navigation system is only depending on the inertial measurements. The RISS is utilizing the odometer/speedometer to measure the vehicle's forward speed. Many types of error affect the odometer measurements. These errors are either due to the vehicle's specifications as the differences in wheel diameters, and/or inefficient wheelbase or the road nature as wheel slips, uneven road surfaces, and/or skidding. In this paper, a Radar-based RISS system is introduced to take place the traditional RISS or INS systems. The radar unit is an essential part of the adaptive cruise control (ACC) system. Furthermore, it is capable of measuring the relative velocity and distance between the carrying and the in front vehicle to reduce collisions and increase the safety of driving. In addition, the radar measurements are not affected by the error sources that affect the odometer. The idea is to invest the ground reflection and derive the forward speed of the onboard vehicle as the ACC keep a safe distance between the cars. A novel method based on extracting the ground reflection features is introduced to obtain the onboard vehicle's speed. The obtained speed is utilized with two accelerometers and one vertical gyroscope to produce the Radar-based RISS system. The proposed system has been integrated with the GPS producing a Radar-based RISS/GPS integrated navigation system. The system has been tested on a real road trajectory in a downtown area and involved several GPS signal outages. The results show the significant capabilities of the proposed system in keeping the navigation solution drift to a minimum especially when the GPS signal is in outage compared with the traditional RISS/GPS system.

Integrated navigation systems have evolved in response to the increasing requirements for more accurate navigation of marine survey vessels. Some systems have been better than others in terms of choice of devices for combination, or in mathematical handling of data from the respective sensors, but all have been inflexible in terms of interchange of sensor types or adaptation of new devices. This paper studies the basic philosophy of navigation system design with primary consideration given to system objectives and control structure. The result is a sensor-independent approach to integrated navigation system design. INTRODUCTION At this point in time, there is no universal aid to navigation which can provide continuous position fixes and velocities on a worldwide, 24-hour per day basis, and still deliver the accuracies required by all users. There are several systems which offer accuracy and continuity, but operate over a limited range; e.g., doppler satellites yield worldwide coverage but give only periodic fix updates; while VLF radio systems yield nearly continuous, worldwide coverage but lack the accuracy required for precision navigation. The Global Positioning System (GPS), promises to give simultaneous solutions to many of these problems, but commercial availability is not likely to be realized before the late 1980's. The approach taken to meet user requirements in precise navigation has been the "integrated navigation system" a combination of two or more different navigation subsystems. This paper deals with the philosophy of integrated system design, reviews the deficiencies in some past approaches to system integration, and describes a design structure which permits flexibility in the choice of sensor subsystems and provides for longer product lifetime. CATEGORIES OF NAVIGATION AIDS Since the earliest days of navigation, mariners have used tools to assist in determining their position (position fix) and in setting and keeping a course over a period of time to reach a desired new position (dead reckoning). Ocean voyages depended upon natural phenomena, with celestial observations for position reference and magnetic compass directions to maintain headings. Local navigation (piloting) has always used line-of-sight reference to coastline features or reference markers to maintain a desired course from successive triangulation bearings. Twentieth century techniques have considerably improved life for the navigator, extending operation on a 24-hour per day, all-weather basis while increasing the accuracy of measurement. Three techniques of measurement form the basis for most of the navigation aids currently in use: radio wave systems, which use broadcast wavelength as a "yardstick" for distance or velocity measurements between the navigator and known reference points; acoustic systems, which perform range or rangerate measurements based on propogation time of sound through water; and gyroscopic systems, which measure orientation and angular velocities within the Earth's gravitational field. The following paragraphs describe systems from all of these categories, giving some specific strengths and weaknesses of each system type.

The constraints of weight, volume and power for Small unmanned air vehicle (UAV) restrict the application of sensors with heavy and good performance and powerful processors. This paper presents a real-time solution of autonomous flight navigation and its results for small UAV by applying small, cheap, low precision and low-power integrated navigation system, which includes Strap-down Inertial Navigation System (SINS) based on Micro-electro-mechanical system (MEMS) inertial sensors, Global Positioning System (GPS) receiver and magnetometer. The Square-Root Unscented Kalman filter (SR-UKF) for data fusion using in this MEMS-SINS/GPS/ magnetometer integrated navigation system provides continuous and reliable navigation results for the loops of guidance and control for the small UAV with autonomous flight. The whole integrated navigation system algorithm is implemented within low-power embedded microprocessors. The real-time flight test results show that the MEMS-SINS/GPS/magnetometer integrated navigation system is effective and accurate.

There are the scale factor error of LDV (laser Doppler velocimeter) and the misalignment between the SINS (Strapdown inertial navigation system) and the vehicle in a SINS/LDV integrated navigation system. In this paper, the effects of these errors on the attitude, velocity and position of dead reckoning are derived, and a new online calibration method aiming to calibrate the scale factor of LDV and the misalignment between the SINS and the vehicle for the integrated system is put forward. This method, which is utilize the velocity and position of the Global Position System (GPS) as references, use the velocity error and position error of dead reckoning to estimate these errors. Through simulation and experiment, the validity and feasibility of the method are verified. The results show that the scale factor and the misalignment can be calibrated with satisfying accuracy, and the related research can provide technical support for high precision navigation of SINS/LDV integrated navigation systems.

FDA's Division of Cooperative Programs (DCP) has used non-computerized instrumentation extensively and proficiently for its specialized coastal water pollution studies that assist state management of shellfish harvest waters. This paper summarizes the instrumentation development portion of a September 1998 fluorometric study in coastal Connecticut. Fluorometry was used to study estuarine dispersion, travel time, and dilution of wastewater treatment plant discharge, yet the computerized hydrography system (CHS) can be used with any instrument that supports real-time ASCII (or NMEA 0183) output. Leading up to this instrumentation development were technology advancements for geographical positioning systems (GPS), fluorometers, portable PCs, electronic nautical charts, and navigation and hydrographic software. Prior to this study, only one off-the-shelf software application (Chartview Pro) was found that had a feature intended to computer log and display instrument data correlated to a plot of the vessel track on electronic nautical charts, both real-time and after the study. Yet this hydrographic feature had not been implemented by an end-user, until FDA-DCP staff developed a computerized hydrography system (CHS) that included Chartview Pro, and the software developer responded to feedback from FDA-DCP instrumentation trials. Stability as well as the responsiveness of the software company were some criteria for the CHS software, as was low cost, and therefore the off-the-shelf appeal. Versatility was also important. A purpose of developing the CHS was to update the hydrography instrumentation used by FDA-DCP and its cooperative program partners.

Fishing activities in the waters of Banyuwangi are relatively intense. Local fishermen often venture 50 nautical miles from the coastline using small boats. These boats are lacking adequate communication and navigation equipment, causing difficulties in obtaining assistance during emergencies. This study aims to develop an Automatic Identification System (AIS) device to be installed on fishing boats. The AIS device developed for this research incorporates the STM32F4 microcontroller, CMX7032 Evaluation Board, VHF Antenna, and Global Positioning System (GPS) as its main components. The integration and configuration of each component will be elaborated in this paper. Performance testing has yielded promising results, as the AIS device was capable of transmitting data up to 10 nautical miles from the Base Station. Utilization of AIS technology would enhance safety and communication among fishermen. Through careful integration and configuration of these components, the AIS device effectively ensures that the fishermen’s positions are accurately tracked and communicated. The successful development and testing of this device underscore its potential to bridge the communication gap, offering timely assistance and enhancing the overall safety of these seafarers.

Το συνέδριο για την ασφάλεια της ζωής στη θάλασσα (SOLAS) που πραγματοποιήθηκε το 1974 ορίζει στον κανονισμό 19/Κεφάλαιο V τον εξοπλισμό ναυσιπλοΐας που μεταφέρεται επί των πλοίων, ανάλογα με τον τύπο τους. Το 2000, ο Διεθνής Ναυτιλιακός Οργανισμός υιοθέτησε μια νέα απαίτηση (ως μέρος ενός αναθεωρημένου νέου κεφαλαίου V) για όλα τα πλοία, να φέρουν συστήματα αυτόματης αναγνώρισης (AIS). Το σύστημα αυτό αποσκοπεί στο καλύτερο και αποτελεσματικότερο έλεγχο της θαλάσσιας κυκλοφορίας από τις αρμόδιες αρχές, αφού τα σήματα που στέλνουν τα πλοία περιέχουν τόσο δυναμικές πληροφορίες όπως η θέση του πλοίου αλλά και στατικές όπως η ταυτότητα του πλοίου. Το εργαστήριο Datastories του Πανεπιστημίου Πειραιά έχει εγκαταστήσει κεραία για την καταγραφή των σημάτων AIS και τη δημιουργία αντίστοιχης βάσης δεδομένων. Επιπλέον, για την καλύτερη διαχείριση και οργάνωση των εργασιών εντός του λιμένα είναι σημαντική η γνώση του Εκτιμώμενου Χρόνου Άφιξης. Στα πλαίσια της παρούσας διπλωματικής θα μελετηθεί η συγκεκριμένη χρονική μεταβλητή. Η μελέτη και η εκτίμηση του χρόνου αυτού γίνεται με τη χρήση νευρωνικού δικτύου, το οποίο θα λαμβάνει ως είσοδο μια σειρά από δεδομένα και ως έξοδο θα δίνει τον εκτιμώμενο χρόνο άφιξης του πλοίου. Τα δεδομένα εισόδου αποτελούνται από τα σήματα AIS που έχουν αποθηκευτεί στη βάση του πανεπιστημίου. Η εκτίμηση του αποτελέσματος πραγματοποιείται με βάση τον πραγματικό χρόνο άφιξης του πλοίου και την απόκλιση από αυτόν. Τέλος, θα μελετηθούν ποιοι παράγοντες μπορούν να επηρεάσουν το αποτέλεσμα, όπως οι καιρικές συνθήκες ή ο χρονικός ορίζοντας των δεδομένων που διαθέτουμε.

The extended Kalman filter (EKF) has been used widely in Global Position System (GPS) and Strapdown Inertial Navigation Systems (SINS) integrated navigation systems,which simply linearizes all nonlinear models.However, careful treatment of the nonlinearity of the system models is particularly critical when the integrated systems use low cost micro-electro-mechanical (MEMS) inertial sensors. Hence application of the EKF in MEMS inertial sensor-based integrated navigation systems will likely lead to inaccurate results. To overcome the shortcomings of the EKF, the unscented Kalman filter (UKF) has been proposed.The UKF does not require the linearization of the system models. Alternatively it uses a set of deterministically selected "sigma-points",which completely capture the true mean and covariance of the original random vector. Then these sigma-points are propagated through the nonlinear models.This captures the mean and covariance to second order accuracy for arbitrary nonlinear functions. In this paper the EKF and UKF are applied in GPS/SINS integrated systems respectively. Simulation result demonstrates that the performance of the UKF is better than the EKF in MEMS inertial sensor-based SINS/GPS integrated systems.