International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / With the rapid development of urban economy, there are bus increasing, route extending, and shuttle frequency increasing etc. At the same time, road construction is subject to land surface, so traffic jam often occurs. It is a big trouble for life of citizens and problem for economy development. So it needs to be improved as fast as possible. Vehicle monitoring system for public traffic in Beijing can expediently monitor the state of each controlled bus, thereby making perfect management. With the integration of GPS, analog trunked communication and digital map, the old, blinding manage system of public traffic would be changed into advanced, visualized management mode, and several routes are dispatched in one dispatch center at the same time. The system frame and its components are introduced in this paper.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper, a devising scheme of Autonomous Vehicle Location and Navigation System is introduced firstly. Then, several key technologies used in the devising scheme are presented, which includes a data fusion method based on extended decentralized kalman filter technology, a map-matching method used to compensate the positioning error, and a digital map data processing method used to realize route planning algorithm. By this time, a sample machine based on the devising scheme introduced in this paper has already been worked out successfully. The availability and the advantages of these technologies have been demonstrated.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The use of Global Positioning System (GPS) receivers as a source to provide Time Space and Position Information (TSPI), and Miss Distance Indication (MDI) data in Test and Evaluation (T&E) applications is being considered. Specifically, GPS receivers are being evaluated to determine their usefulness as a sensor in a Sidewinder missile telemetry system (AN/DKT-80). Initial testing has indicated that position information generated from a GPS receiver can provide significantly better position data than a radar tracking system when using Double Differential error correction techniques. This concept requires a GPS reference station to be located in the general proximity of the Telemetry data-receiving site. Software has been developed that will compare GPS data from the airborne telemetry system to the GPS reference station and display a real-time TSPI solution. This software will also provide MDI information from two different airborne sources that are equipped with GPS receivers (missile and drone). To prove out this concept, a Commercial Off the Shelf (COTS) Commercially/Available (C/A) code GPS receiver was integrated into the AN/DKT-80 Sidewinder telemetry system (TM). A MQM-107 drone was instrumented with the same GPS receiver, as was a ground based reference station. A simple TM was developed for the drone that telemeters only the GPS data. The modified AN/DKT-80 system incorporated an Inertial Measurement Unit (IMU) into the design. Post processing software was developed that will integrate the IMU information with the GPS data so accurate position can be generated if the GPS data was momentarily lost. A missile firing is scheduled for the spring of 1999 to prove this concept.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / The Joint Advanced Missile Instrumentation (JAMI) program is developing a Time, Space, and Position Information (TSPI) unit for high dynamic missile platforms by employing the use of Global Position System (GPS) and inertial sensors. The GPS data is uncoupled from the inertial data. The output of the JAMI TSPI unit follows the packet telemetry protocol and is called the TSPI unit message structure (TUMS). The packet format allows the data stream to stand on its own, be integrated into a packet telemetry system or be an asynchronous data channel in a PCM data stream. On the ground, the JAMI data processor (JDP) Kalman filters the GPS and inertial data to provide a real time TSPI solution to the ranges for display. This paper gives an overview of the message format, the timing relationships between the GPS data and inertial data, and how TUMS is to be handled by the telemetry receiving site to hand it off to the JDP.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / The Joint Advance Missile Instrumentation (JAMI) program has developed a Time Space Position Information (TSPI) unit (JTU). The JTU employs a novel use of Global Positioning System (GPS) technology, and inertial measurement units (IMU) to provide a real time trajectory for high dynamic missile systems. The GPS system can function during high g maneuvers that an air-to-air missile might encounter. The IMU is decoupled from the GPS sensor. The IMU data is a secondary navigation source for the JTU and will provide platform attitude. The GPS data and IMU data are sent to the ground in telemetry packet called TSPI Unit Message Structure (TUMS). The TUMS packet is sent to a computer that hosts the JAMI Data Processing (JDP) software, which performs a Kalmam filter on the GPS and IMU data to provide a real time TSPI solution to the range displays. The packetized TUMS data is available in three different output formats: RS-232 serial data, 16-bit parallel and PCM. This paper focuses on how to integrate the JTU into a telemetry system, use it as a standalone system, and provides examples of possible uses.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / The Joint Advanced Missile Instrumentation (JAMI) Program involves the integration of Global Positioning System (GPS) tracking technology into the Test Ranges. GPS Technology will be used for Time, Space, and Position Information (TSPI) as well as Flight Termination purposes. JAMI is currently developing the JAMI TSPI Unit (JTU) and the Flight Termination Safe & Arm (FTS&A) devices. This paper will discuss the current efforts to integrate these JAMI components, off the shelf items (Flight Termination Receivers (FTR), Telemetry Transmitters, Encryptor and Thermal Batteries) and in-house developed devices (PCM Encoder, Tri-band Antenna with integrated Limiter, Filter, and Amplifier) into a five-inch diameter Missile Telemetry (TM) Section. The discussion of the transmission of the data and how the Test Ranges process it is beyond the scope of this paper and is covered in [1].

With sales reaching $4.4 billion dollars in the first half of 2006 in the United States alone, and an estimated 80% of the world receiving coverage for their wireless phones in that year, interest in these devices as more than mere communicators has greatly increased. In the mid-to-late 1990s, digital cameras began to be incorporated into cellphones, followed shortly thereafter by Global Positioning System (GPS) hardware allowing location-based services to be offered to customers. Since then the use of mobile phone hardware for non-communication purposes has continued to expand. Some models, such as the Motorola V3M, have been specifically geared toward the storage and display of music and visual media, as well as receiving Internet broadcasts. It is perhaps surprising, therefore, that relatively little has been done from an academic standpoint to provide a qualitative and comprehensive method of evaluating the performance of mobile phones regarding their ability to function as computing devices. While some manuals do offer comparisons of Application Programming Interfaces (APIs) that aid in the development of cellphone applications, little documentation exists to provide objective measurements of performance parameters. This dissertation proposes a framework for evaluating the performance of mobile phones from a computational angle, focusing on three criteria: the processing power of the Central Processing Unit (CPU), data transfer capabilities, and the performance of the phone's GPS functionality for the appropriation of geographic location data. Power consumption has always been a major source of interest in the study of computer systems, and the limited hardware resources of mobile devices such as laptop computers, Personal Data Assistants (PDAs) and cellular telephones makes this a key concern. The power consumption factors associated with operation are therefore considered alongside the three core criteria being studied in this framework. In addition to framework design, software tools for the evaluation of cellphones were also developed, and these were applied to a test case of the Sanyo SCP-7050 model. This provides an example of the utility of the framework in evaluating existing phone models and a foundation for the assessment of new models as they are released.

Vehicle self-localization, the ability of a vehicle to determine its own location, is vital for many aspects of Intelligent Transportation Systems (ITS) and telematics where it is often a building block in a more complex system. Navigation systems are perhaps the most obvious example, requiring knowledge of the vehicle's location on a map to calculate a route to a desired destination. Other pervasive examples are the monitoring of vehicle fleets for tracking shipments or dispatching emergency vehicles, and in public transit systems to inform riders of time-of-arrival thereby assisting trip planning. These system often depend on Global Positioning System (GPS) technology to provide vehicle localization information; however, GPS is challenged in urban environments where satellite visibility and multipath conditions are common. Vehicle localization is made more robust to these issues through augmentation of GPS-based localization with complementary sensors, thereby improving the performance and reliability of systems that depend on localization information. This thesis investigates the augmentation of vehicle localization systems with visual context. Positioning the vehicle with respect to objects in its surrounding environment in addition to using GPS constraints the possible vehicle locations, to provide improved localization accuracy compared to a system relying solely on GPS. A modular system architecture based on Bayesian filtering is proposed in this thesis that enables existing localization systems to be augmented by visual context while maintaining their existing capabilities. It is shown in this thesis that localization errors caused by GPS signal multipath can be reduced by positioning the vehicle with respect to visually-detected intersection road markings. This error reduction is achieved when the identities of the detected road marking and the road being driven are known a priori. It is further shown how to generalize the approach to the situation when the identities of these parameters are unknown. In this situation, it is found that the addition of visual context to the vehicle localization system reduces the ambiguity of identifying the road being driven by the vehicle. The fact that knowledge of the road being driven is required by many applications of vehicle localization makes this a significant finding. A related problem is also explored in this thesis: that of using vehicle position information to augment machine vision. An approach is proposed whereby a machine vision system and a vehicle localization system can share their information with one another for mutual benefit. It is shown that, using this approach, the most uncertain of these systems benefits the most by this sharing of information. Augmenting vehicle localization with visual context is neither farfetched nor impractical given the technology available in today's vehicles. It is not uncommon for a vehicle today to come equipped with a GPS-based navigation system, and cameras for lane departure detection and parking assistance. The research in this thesis brings the capability for these existing systems to work together.

Vehicle self-localization, the ability of a vehicle to determine its own location, is vital for many aspects of Intelligent Transportation Systems (ITS) and telematics where it is often a building block in a more complex system. Navigation systems are perhaps the most obvious example, requiring knowledge of the vehicle's location on a map to calculate a route to a desired destination. Other pervasive examples are the monitoring of vehicle fleets for tracking shipments or dispatching emergency vehicles, and in public transit systems to inform riders of time-of-arrival thereby assisting trip planning. These system often depend on Global Positioning System (GPS) technology to provide vehicle localization information; however, GPS is challenged in urban environments where satellite visibility and multipath conditions are common. Vehicle localization is made more robust to these issues through augmentation of GPS-based localization with complementary sensors, thereby improving the performance and reliability of systems that depend on localization information. This thesis investigates the augmentation of vehicle localization systems with visual context. Positioning the vehicle with respect to objects in its surrounding environment in addition to using GPS constraints the possible vehicle locations, to provide improved localization accuracy compared to a system relying solely on GPS. A modular system architecture based on Bayesian filtering is proposed in this thesis that enables existing localization systems to be augmented by visual context while maintaining their existing capabilities. It is shown in this thesis that localization errors caused by GPS signal multipath can be reduced by positioning the vehicle with respect to visually-detected intersection road markings. This error reduction is achieved when the identities of the detected road marking and the road being driven are known a priori. It is further shown how to generalize the approach to the situation when the identities of these parameters are unknown. In this situation, it is found that the addition of visual context to the vehicle localization system reduces the ambiguity of identifying the road being driven by the vehicle. The fact that knowledge of the road being driven is required by many applications of vehicle localization makes this a significant finding. A related problem is also explored in this thesis: that of using vehicle position information to augment machine vision. An approach is proposed whereby a machine vision system and a vehicle localization system can share their information with one another for mutual benefit. It is shown that, using this approach, the most uncertain of these systems benefits the most by this sharing of information. Augmenting vehicle localization with visual context is neither farfetched nor impractical given the technology available in today's vehicles. It is not uncommon for a vehicle today to come equipped with a GPS-based navigation system, and cameras for lane departure detection and parking assistance. The research in this thesis brings the capability for these existing systems to work together.

This thesis describes the theoretical and practical stages through development to testing of an integrated navigation system, specifically composed of an Inertial Navigation System (INS), and Global Positioning System (GPS). Integrated navigation systems combine the best features of independent systems to bring out increased performance, improved reliability and system integrity. In an integrated INS/GPS system, INS output is used to calculate current navigation states / GPS output is used to supply external measurements, and a Kalman filter is used to provide the most probable corrections to the state estimate using both data. Among various INS/GPS integration strategies, our aim is to construct a tightly coupled integrated INS/GPS system. For this purpose, mathematical models of INS and GPS systems are derived and they are linearized to form system dynamics and system measurement models respectively. A Kalman filter is designed and implemented depending upon these models. Besides these, based on the given aided navigation system representation a quantitative measure for observability is defined using Gramians. Finally, the performance of the developed system is evaluated with real data recorded by the sensors. A comparison with a reference system and also with a loosely coupled system is done to show the superiority of the tightly coupled structure. Scenarios simulating various GPS data outages proved that the tightly coupled system outperformed the loosely coupled system from the aspects of accuracy, reliability and level of observability.