On sensor fusion for airborne wind energy systems

A study on filtering aspects of airborne wind energy generators is presented. This class of renewable energy systems aims to convert the aerodynamic forces generated by tethered wings, flying in closed paths transverse to the wind flow, into electricity. The accurate reconstruction of the wing's position, velocity and heading is of fundamental importance for the automatic control of these kinds of systems. The difficulty of the estimation problem arises from the nonlinear dynamics, wide speed range, large accelerations and fast changes of direction that the wing experiences during operation. It is shown that the overall nonlinear system has a specific structure allowing its partitioning into sub-systems, hence leading to a series of simpler filtering problems. Different sensor setups are then considered, and the related sensor fusion algorithms are presented. The results of experimental tests carried out with a small-scale prototype and wings of different sizes are discussed. The designed filtering algorithms rely purely on kinematic laws, hence they are independent from features like wing area, aerodynamic efficiency, mass, etc. Therefore, the presented results are representative also of systems with larger size and different wing design, different number of tethers and/or rigid wings.Comment: This manuscript is a preprint of a paper accepted for publication on the IEEE Transactions on Control Systems Technology and is subject to IEEE Copyright. The copy of record is available at IEEEXplore library: http://ieeexplore.ieee.org

Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Fusion of sensor information to measure the total energy of an aircraft and provide information about flight performance and local microclimate

The application of using Unmanned Aerial Vehicles (UAVs) to locate thermal updraft currents is a relatively new topic. It was first proposed in 1998 by John Wharington, and, subsequently, several researchers have developed algorithms to search and exploit thermals. However, few people have physically implemented a system and performed field testing. The aim of this project was to develop a low cost system to be carried on a glider to detect thermals effectively. A system was developed from the ground up and consisted of custom hardware and software that was developed specifically for aircraft. Data fusion was performed to estimate the attitude of the aircraft; this was done using a direction cosine (DCM) based method. Altitude and airspeed data were fused by estimating potential and kinetic energy respectively; thus determining the aircraft's total energy. This data was then interpreted to locate thermal activity. The system comprised an Inertial Measurement Unit (IMU), airspeed sensor, barometric altitude sensor, Global Positioning System (GPS), temperature sensor, SD card and a realtime telemetry link. These features allowed the system to determine aircraft position, height, airspeed and air temperature in realtime. A custom-designed radio controlled (RC) glider was constructed from composite materials in addition to a second 3.6 m production glider that was used during flight testing. Sensor calibration was done using a wind tunnel with custom designed apparatus that allowed a complete wing with its pitot tube to be tested in one operation. Flight testing was conducted in the field at several different locations over the course of six months. A total of 25 recorded flights were made during this period. Both thermal soaring and ridge soaring were performed to test the system under varying weather conditions. A telemetry link was developed to transfer data in realtime from the aircraft to a custom ground station. The recorded results were post-processed using Matlab and showed that the system was able to detect thermal updrafts. The sensors used in the system were shown to provide acceptable performance once some calibration had been performed. Sensor noise proved to be problematic, and time was spent alleviating its effects. Results showed that the system was able to measure airspeed to within ± 1 km/h. The standard deviation of the altitude estimate was determined to be 0.94 m. This was deemed to be satisfactory. The system was highly reliable and no faults occurred during operation. In conclusion, the project showed that inexpensive sensors and low power microcontrollers could be used very effectively for the application of detecting thermals

All Source Sensor Integration Using an Extended Kalman Filter

The global positioning system (GPS) has become an ubiquitous source for navigation in the modern age, especially since the removal of selective availability at the beginning of this century. The utility of the GPS is unmatched, however GPS is not available in all environments. Heavy reliance on GPS for navigation makes the warfighter increasingly vulnerability as modern warfare continues to evolve. This research provides a method for incorporating measurements from a massive variety of sensors to mitigate GPS dependence. The result is the integration of sensor sets that encompass those examined in recent literature as well as some custom navigation devices. A full-state extended Kalman filter is developed and implemented, accommodating the requirements of the varied sensor sets and scenarios. Some 19 types of sensors are used in multiple quantities including inertial measurement units, single cameras and stereo pairs, 2D and 3D laser scanners, altimeters, 3-axis magnetometers, heading sensors, inclinometers, a stop sign sensor, an odometer, a step sensor, a ranging device, a signal of opportunity sensor, global navigation satellite system sensors, an air data computer, and radio frequency identification devices. Simulation data for all sensors was generated to test filter performance. Additionally, real data was collected and processed from an aircraft, ground vehicles, and a pedestrian. Measurement equations are developed to relate sensor measurements to the navigation states. Each sensor measurement is incorporated into the filter using the Kalman filter measurement update equations. Measurement types are segregated based on whether they observe instantaneous or accumulated state information. Accumulated state measurements are incorporated using delayed-state update equations. All other measurements are incorporated using the numerically robust UD update equations

An aircraft and provide information about flight performance and local microclimate

Includes abstract.Includes bibliographical referencesThe application of using Unmanned Aerial Vehicles (UAVs) to locate thermal updraft currentsis a relatively new topic. It was first proposed in 1998 by John Wharington, and, subsequently, several researchers have developed algorithms to search and exploit thermals. However, few people have physically implemented a system and performed field testing. The aim of this project was to develop a low cost system to be carried on a glider to detect thermals effectively. A system was developed from the ground up and consisted of custom hardware and software that was developed specifically for aircraft. Data fusion was performed to estimate the attitude of the aircraft; this was done using a direction cosine (DCM) based method. Altitude and airspeed data were fused by estimating potential and kinetic energy respectively; thus determining the aircraft’s total energy. This data was then interpreted to locate thermal activity. The system comprised an Inertial Measurement Unit (IMU), airspeed sensor, barometric altitude sensor, Global Positioning System (GPS), temperature sensor, SD card and a realtime telemetry link. These features allowed the system to determine aircraft position, height, airspeed and air temperature in realtime. A custom-designed radio controlled (RC) glider was constructed from composite materials in addition to a second 3.6 m production glider that was used during flight testing. Sensor calibration was done using a wind tunnel with custom designed apparatus that allowed a complete wing with its pitot tube to be tested in one operation. Flight testing was conducted in the field at several different locations over the course of six months. A total of 25 recorded flights were made during this period. Both thermal soaring and ridge soaring were performed to test the system under varying weather conditions. A telemetry link was developed to transfer data in realtime from the aircraft to a custom ground station. The recorded results were post-processed using Matlab and showed that the system was able to detect thermal updrafts. The sensors used in the system were shown to provide acceptable performance once some calibration had been performed. Sensor noise proved to be problematic, and time was spent alleviating its effects

Non-GNSS Smartphone Pedestrian Navigation Using Barometric Elevation and Digital Map-Matching

Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable for many applications. This article presents a real-time, self-contained outdoor navigation application that uses only the existing sensors on a smartphone in conjunction with a preloaded digital elevation map. The core algorithm implements a particle filter, which fuses sensor data with a stochastic pedestrian motion model to predict the user’s position. The smartphone’s barometric elevation is then compared with the elevation map to constrain the position estimate. The system developed for this research was deployed on Android smartphones and tested in several terrains using a variety of elevation data sources. The results fromthese experiments showthe systemachieves positioning accuracies in the tens of meters that do not grow as a function of time