Guidance and Control for Flat-Circular Parachutes

This paper evaluates the performance of a semidistributed multinode time-of-arrival (TOA) anddirection-of-arrival (DOA) fusion localization technique in terms of localization circular error probability (CEP). The localization technique is applicable in mobile ad hoc networks (MANETs) when global positioning system (GPS) is not available (GPS denied environments). The localization CEP of the technique is derived theoretically and verified via simulations. In addition, we theoretically derive the localization CEP of GPS-aided TOA fusion and GPS-aided DOA fusion techniques, which are also applicable in MANETs. Finally, we compare these three localization techniques theoretically and via simulations. The comparison confirms that in moderate scale MANETs, the multinode TOA-DOA fusion localization technique achieves the best performance; while in large scale MANETs, GPS-aided TOA fusion leads to the best performance.

Global positioning system (GPS) technologies have improved the ability of researchers to monitor wildlife; however, use of these technologies is often limited by monetary costs. Some researchers have begun to use commercially available GPS loggers as a less expensive means of tracking wildlife, but data regarding performance of these devices are limited. We tested a commercially available GPS logger (i–gotU GT–120) by placing loggers at ground control points with locations known to < 30 cm. In a preliminary investigation, we collected locations every 15 minutes for several days to estimate location error (LE) and circular error probable (CEP). Using similar methods, we then investigated the influence of cover on LE, CEP, and fix success rate (FSR) by constructing cover over ground control points. We found mean LE was < 10 m and mean 50% CEP was < 7 m. FSR was not significantly influenced by cover and in all treatments remained near 100%. Cover had a minor but significant effect on LE. Denser cover was associated with higher mean LE, but the difference in LE between the no cover and highest cover treatments was only 2.2 m. Finally, the most commonly used commercially available devices provide a measure of estimated horizontal position error (EHPE) which potentially may be used to filter inaccurate locations. Using data combined from the preliminary and cover investigations, we modeled LE as a function of EHPE and number of satellites. We found support for use of both EHPE and number of satellites in predicting LE; however, use of EHPE to filter inaccurate locations resulted in the loss of many locations with low error in return for only modest improvements in LE. Even without filtering, the accuracy of the logger was likely sufficient for studies which can accept average location errors of approximately 10 m.

Low-Cost Livestock Global Positioning System Collar from Commercial Off-the-Shelf Parts

Control of a quadrotor helicopter using the COMPASS (BeiDou) system and on-board vision system

This paper presents the current design status and some preliminary calibration/performance analyses of the prototype of a multi-sensor personal navigator currently under development at The Ohio State University. The main purpose of this research project is to develop a theoretical foundation and algorithms which integrate the Global Positioning System (GPS), Micro-electro-mechanical inertial measurement unit (MEMS IMU), barometer and compass to provide seamless position information to support navigation and tracking of ground military and rescue personnel. The system is designed with an open-ended architecture, which would be able to incorporate additional navigation and imaging sensor data, extending the system's operations to the indoor environments. The current target accuracy of the system is at 3–5 m CEP (circular error probable). In the current prototype implementation, the following sensors are integrated in the tightly coupled Extended Kalman Filter (EKF): GPS carrier phase and pseudorange data, Crossbow MEMS IMU400C, PTB220A barometer, and KVH Azimuth 1000 digital compass. This paper focuses on the design architecture of the integrated system and the preliminary performance analysis, with a special emphasis on the navigation during the loss of GPS signal. A brief description of the individual sensors and their calibration is presented, together with the navigation performance of the system of sensors.

As a supplement to the Global Positioning System (GPS) in an urban center and indoor environment, the digital television (DTV) segment sync signal can be employed to obtain a mobile user’s position. Two DTV receivers and a counter are integrated to measure the time difference of arrival (TDOA) for a pair of received signals from a transmitter and its corresponding repeater (DTVR). Using the measurements from a transmitter and its multiple corresponding DTVR pairs, the mobile user position can be estimated using the recursive least square method. An experiment done in Seoul using two low-grade high resolution digital television (HDTV) receivers and a two-channel universal counter demonstrates that the mean value of the mobile user position measurement is accurate to 42.58 meters circular error probability (CEP).

Sowing failure or poor emergence due to limited rainfall is a serious problem for crop production in arid and semiarid regions in north China. The objective of this study was to design a variable rate precision irrigating hill-seeder, which could change the amount of irrigating water automatically according to the soil moisture content of the field. A control system integrating single-chip computer, Global Positioning System (GPS), Geographic Information System (GIS) and variable rate application (VRA) technologies was developed. The system employed a high speed single-chip W78E58 unit as the control center, a high capacity U-disk for GIS data transfer, and a GPS receiver as the locating device. The system could detect a falling seed through a photoelectric sensor installed inside the collector of the seeder and then open an electromagnetic valve to control water delivery so that the seed and water could fall at the same time and place. The amount of water was determined by the minimum soil moisture content required for seed germination. The control system was adapted to a maize hill seeder. A static calibration experiment showed that the controller had very good linearity. The detection rate of the photoelectric sensor for maize seeds reached above 99%, indicating that the control system had high control accuracy.

This paper presents an alternate recursive state estimator of moving horizon estimation as compared to the conventional state estimator of Kalman filtering. The state estimator estimates the position set, velocity set and attitude data of the dynamic aerial vehicle. In the first scenario, the available data for processing are the measurement set from accelerometers assembly, gyroscope triad, and global positioning system (GPS) from the low cost inertial measuring unit (IMU). The GPS position and GPS velocity measurements are the aiding source as well the comparison reference of the computed solution of the dynamic aerial vehicle (DAV). In the second scenario receding window discrete time state estimator, extended for non-linear vehicle navigation application is implemented using the deterministic cost function of least squares, for integrated filtering. The receding data window approach uses the past measurements samples over the horizon as the tuning parameter of the moving horizon state estimator. The moving horizon state estimator is evaluated offline in the numerical experiment including the flight testing data collected. The flight test on a small aerial vehicle with all the sensors, GPS receiver, power systems instrumented onboard is considered for this paper. Matlab platform is used to simulate the noise environment and implementing the algorithms. This paper designed algorithm results reveals that proposed moving horizon estimator is faster in convergence in the presence of large initialization errors, linearization errors and outliers as compared to the reference filter i.e. EKF tested online and offline.

The authors discuss the design of a limiting filter, a new type of microwave circuit device that is essentially a filter modified by the addition of PIN diodes or other protection devices that give the filter nonlinear limiting properties in its passband. In one potential application, for protecting the front end of a microwave receiver, a limiting filter would prevent receiver interference from out-of-band signals, as well as avoid receiver upset or damage by limiting in-band RF transients. The design specifications for the front end of a commercial global positioning system (GPS) receiver were used as a guideline for designing the limiting filter. Measurements of the prototype limiting filter are compared to theoretical calculations, and rather good agreement with measurements is observed. The measured results show that the limiting filter with diodes on the first and last resonators has characteristics that are essentially identical to those of a standard filter of the same type at low power levels, but begins limiting at 0.1 dBm and obtains greater than 30-dB isolation at power levels above 0.5 W. >

The global positioning system (GPS) can be utilised to detect ground deformations of the surface of a volcano. Ground deformation monitoring is considered one of the most effective tools for investigating the behaviour of active volcanoes. The decreasing cost of GPS hardware, together with the increased reliability of the technology, facilitates such demanding applications. GPS ground deformation measurements can be continuous, automatic, conducted in all weather conditions, and provide three-dimensional positioning results. Higher computing power also means that the complex mathematics required to process GPS baselines can be easily handled in near real time. During the past few years a methodology has been developed for processing data collected by GPS networks consisting of a mixed set of single-frequency and dual-frequency receivers. The strategy is to deploy a few permanent, ‘fiducial’ GPS stations with dual-frequency, geodetic-grade receivers surrounding an ‘inner’ network of low-cost, single-frequency GPS receivers. Such a configuration offers considerable flexibility and cost savings for geodynamic applications such as volcano deformation monitoring, which require a dense spatial coverage of GPS stations, and where it is not possible to establish permanent GPS networks using only expensive dual-frequency instrumentation. This configuration has recently been tested at the Mt. Papandayan volcano in West Java, Indonesia. The two-stage network design consists of an inner network of four single-frequency Canadian Marconi (CM) GPS receivers surrounded by three dual-frequency Leica CRS1000 GPS receivers. The inner network logged and transmitted GPS data from the ‘slave’ stations located on the volcano, to a base station. The combined processing of the CM and Leica receiver data was performed off-line so as to investigate the performance of such a mixed-mode system. The basis of the processing methodology is to separate the dual-frequency, ‘fiducial’ station data processing from the baseline processing involving the single-frequency receivers on the volcano. The data processing for the former was carried out using a modified version of the Bernese software, to generate a file of ‘corrections’ (analogous to Wide Area DGPS correction models for the distance dependent biases – primarily due to atmospheric refraction). These ‘corrections’ were then applied to the double-differenced phase observations from the inner receivers to improve the baseline accuracies. A description of the field testing (and its challenges) during February–March 2000, together with a discussion of some of the results are presented.

This paper presents a model to predict the GDOP value (Geometric Dilution of Precision) and the probability of its occurrence at a point in space and time using airborne LiDAR (Light Detection and Ranging) data and the ultra-rapid product (URP) available from the International GPS Service. LiDAR data help to classify the terrain around a GPS (Global Positioning System) receiver into categories such as ground, opaque objects, translucent objects and transparent regions as per their response to the transmission of GPS signal. Through field experiments it is established that URP can be used satisfactorily to determine GDOP. Further experiments have shown that the translucent objects (mainly trees here) lower the GDOP quality as they obstruct the GPS signal. LiDAR data density on trees is used as a measure of the translucency of trees to the GPS signal. Through GPS observations taken in field a relationship has been established between LiDAR data density on trees and the probability that a satellite which is behind the tree is visible at the GPS receiver. A model is presented which, for all possible combinations of visible satellites, computes the GDOP value along with the probability of occurrence of this GDOP. A few results are presented to show the performance of the model developed and its possible application in location based queries.

This paper gives a structure of the software Global Positioning System (GPS) receiver and details the use of matched filter in the acquisition unit. With this new architecture, the GPS receiver is able to acquire 3 satellites simultaneously without any increase in hardware, and save the mean acquisition time to about 1/3. To further reduce the area and power consumption, several strategies have been employed in the design of matched filter. The final chip of the software GPS receiver is fully tested and already tapped out. The implementation result will be back in September 2005

While GPS (Global Positioning System) navigation and GPS based autonomous car driving techniques are mature, the security of GPS signal has not been a primary system concern. In fact, it has been shown that an ordinary GPS can be easily spoofed by a low-cost, open-source based software defined radio (SDR) system such as bladeRF and HackRF [3, 4] which can cause serious complications to the navigation system of the car especially for self-driving cars which are driven based on the information from sensors, cameras, and GPS. In this work, we design a new GPS authentication system called lightweight authentication GPS (AuthGPS) to authenticate GPS signal against GPS spoofing and LTE base station broadcast message spoofing. In the past, there have been many successful attempts on GPS spoofing which resulted in shifting the destination of the car to the spoofer's desired location. In a case where the car is connected to the Internet via LTE network, the navigation system can find out if the GPS is spoofed by acquiring the correct GPS satellite information from LTE base stations' location information. However, a skillful attacker can spoof the LTE base station signals [7] as well using another SDR which will produce spoofed LTE base station information. Hence giving wrong information about GPSinformation according to the will of the attacker. Currently, there are defense methods against the GPS spoofing [6]. One of them is signal-processing-based methods. By monitoring unusual or unreasonable signal changes at GPS receivers, GPS spoofing attack can be detected. Received Power Monitoring (RPM) looks at all the received amplitude and automatic gain control (AGC) setpoint [1]. The receiver will sense drastic power jump if a spoofing attack occurs. However, an overly powerful spoofing attack with noise is not detectable in the case of this mechanism. Another way to detect spoofing is the symmetric-key encryption mechanism of GPS signals. According to previous research [2], encrypted precision code for anti-spoofing referred to as P(Y) code, might not be able to be spoofed. A spoofing attack can be detected by calculating cross-correlation between spoofed coarse/acquisition code, referred to as C/A code, and P(Y) code. Unfortunately, this P(Y) code is only for military purpose while the C/A code can be publicly accessible. This method requires knowledge of specific key which is not revealed to the public to decrypt P(Y) code. Monitoring the direction of arrival of the signals can be one of the methods [6]. A GPS receiver measures the direction-of-arrival vector with more than 3 antennas. Even though this signal-geometrybased system with multiple antennas makes GPS robust, an attacker can spoof signals from multiple directions, which is more difficult to detect the spoofing. The idea here is to develop a system that can discriminate the spoofed signal without complex computation or heavy message exchange. An important component of AuthGPS is a verification of valid GPS satellite information via LTE base stations' location information. We propose 6-digit one-time password-based authentication system in this paper.

Position determination using satellite navigation system has grown significantly. It provides geospatial with global coverage called GNSS (Global Navigation System Satellite). GNSS satellites consists of GLONASS, GPS (Global positioning system) and Galileo.GPS is the most commonly used system and it is known to its capability to determine 3D position on the surface of the earth. In order to determine the position, a GPS receiver must be able to receive signals from at least four GPS satellites. However, the determination of position in condensed areas such as tunnels, area surrounded by high rise buildings, highly forested and in other closely-knit areas is not achieved because satellite signals cannot reach the receiver in the above-mentioned areas and also others where the signals are reflected before being received by a GPS receiver. In this paper, we present the algorithm to fuse GPS and the inertial measurement unit (IMU) to enable positioning in the above-mentioned Condensed Areas. The standard deviations of the two measurements show that GPS-IMU is better than GPS alone, the standard deviation when satellite outages occurred is - 4.57475 for GPS-IMU measurements and 0.218675 for GPS observations. We presented the results in graphics and it shows that GPS measurements are easily disturbed by external influence such as multipath but GPS-IMU graphic is continuous and robust. The advantages and disadvantages of GPS and INS are complementary and make them work together to enable the accurate measurements in the areas mentioned above. Integration of INS and GNSS can be classified into three types, loosely coupled Kalman filter, tightly coupled Kalman filters and ultratight coupled Kalman filter. In this research we used loosely coupled Kalman filter and tightly coupled Kalman filters to combine GPS and INS in one system.

This paper presents a motion planning, guidance and control system for an Autonomous surface vessel in a practical maritime environment. The motion planning algorithm is based in the angle-guidance fast marching square method and the guidance system is based in the line-of-sight trajectory tracking algorithm. To validate the motion planning algorithm, numerical simulations were carried out to compute the optimal path in a static environment including various obstacles. The guidance system was tested with an autonomous surface vehicle tracking a pre-established trajectory including static obstacles. The autonomous surface vehicle is a self-propelled scaled ship model of 2.5 m equipped with sensors and actuators, inertial measurement unit, GNSS positioning system, propulsion DC motors, and wireless communication. From the experiments and numerical simulations, a good agreement was found.