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American Institute of Aeronautics and Astronautics

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Modular UAV Students Project

Petr Adamek1, Jaroslav Halgasik2, Josef Novak3, Petr Pahorecky4

Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Control Engineering, Technicka 2, 166 27 Prague, Czech Republic

The report is devoted to a modular UAV project conducted jointly by the students of mechanical and electrical engineering at the Czech Technical University in Prague (CTU), and in cooperation with the Aerospace Research and Test Establishment (VZLU) in Prague. The purpose of the project is to design, develop and produce a small autonomous flying vehicle. There has been significant grow of popularity of all kinds of Unmanned Aerial Systems over the past few years. The reason is simple – price. There are many areas of aerial works that can be done by UAS. These include aerial photography, traffic monitoring, agriculture, military and others. UAS developed and targeted by this project is ment to be used primarily as a flying platform for subsequent research and educational activities by CTU and VZLU staff. The project involves construction of a flight mechanics mathematical model, simulation of dynamical behavior, development of a control hardware unit, design of control laws, mechanical construction of the aircraft and the flight tests and measurements at the final foreseen stage. Modularity of the mechanical design, hardware components as well as the software components is the main theme throughout the project.

Nomenclature AHRS = Attitude and Heading Reference System AC = Aerodynamic Center CD = drag coefficient CG = Center of Gravity Cy = lift coefficient in y axis direction CL = lift coefficient in z axis – perpendicular axis to flight axis Cl = moment coefficient in x axis direction Cm = moment coefficient in y axis direction Cn = moment coefficient in z axis direction DMP = Digital Motion Processor GCS = Ground Control Station GPS = Global Positioning System IMU = Inertial Measurement Unit LQ = Linear-quadratic regulator MAC = Mean Aerodynamic Chord MEMS = Micro-Electro-Mechanical Systems MTOW = Maximum take-off weight NP = Neutral Point PCB = Printed circuit board PID = Proportional-integral-derivative controller RC = Radio Control UAV = Unmanned Aerial Vehicle V = Air speed

1 Master student of Aerospace Engineering, Faculty of Mechanical Engineering, [email protected] 2 Master Student of Aircraft and Space Systems, Faculty of Electrical Engineering, [email protected] 3 Master Student of Aircraft and Space Systems, Faculty of Electrical Engineering, [email protected] 4 Master Student of Aircraft and Space Systems, Faculty of Electrical Engineering, [email protected]


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I. Introduction OTIVATION to create a new low cost UAS came from Department of Aerodynamics, Aeronautics Research and Test Establishment (or VZLU) in Prague. Team of three students, one from Faculty of Mechanical

Engineering and two from Faculty of Electrical Engineering are involved in the project. Secondary impuls for this students project comes from research and educational activities at the Department of Control Engineering, FEE CTU, focused on flight dynamics, flight control systems, control laws design for aerospace applications, and formation flying control algorithms. Both the theoretical research conducted at the Department, and related university courses and diploma MSc. projects given and supervised by the Department experts, can certainly strongly benefit from experimental verification possibilities. For this purpose, one must ensure that the selected solution offers broad flexibility, tweakability and opennes suitable for expected necessary modifications of the control system as new chalanges appear during all the phases of a particular project in mind - updated requirements on flight performance and FCS functionalities, new/modified communication devices to be incorporated, specification/refinement of communication protocols for high-level agent-based formation and mission controls, etc. These aspects naturally call for a complete custom-built solution of the flight control unit. The discussed students UAV project is therefore suitable for these purposes. This initiative is aimed at development, realization and testing of a low-cost lightweight on-board hardware platform for RC-size aircraft, equipped with standard sensors and actuator drivers sets, microchip computer with dedicated software routines, and related ground station. All software and hardware solutions are fully developed in-the-house by the team members. The prototype has been tested during flight in June 2012 with a delta-wing foam A/C model and it performed very well and flawlessly. For the aircraft design, number of preliminary specifications have been set:

• Ability of autonomous flight • Forward looking camera placed on remotely controlled tilt platform • Minimal endurance 30 minutes • Maximum weight 10 kg • Unconventional construction • Maximum wing span of 2 m and space to install 6-component internal balance, so that the flying prototype

can be tested in 3 m Low Speed Wind Tunnel at VZLU The paper is organized as follows. The following Section II is devoted to aircraft design and configuration specifications. Section III and IV evaluates the performances and power requierementsof the design. Section V presents the mathematical model. Starting from section VI, technical requirements and details of HW solution of flight control unit are presented.

II. Aircraft Design and Configuration After evaluating of a number of existing Unmanned Aerial Vehicles (Table 1) and weight of different

components it has been determined that design maximum take-off weight will be 4 kg. The speed range has been determined to start at as low as 36 kph, or 10 mps and go up to maximum speed of more than 100 kph.

Aircraft Manufacturer Country Wingspan Length High

[m] [m] [m]

AZIMUT 2 Alcore Technologies SA France 2,9 1,8 0,3

BIODRONE Alcore Technologies SA France 3,4 1,8 0,3

DVF 2000 Survey Copter France 3 1,2

SPERWER B SAGEM France 6,8 3,9 1,3

DRDO RUSTOM DRDO India 7,9 5,12 2,4

ORBITER Aeronautics Ltd. Israel 2,2 1 0,2

BOOMERANG Bluebird Aero Systems Israel 2,7 1,1 0,4

SKYLARK 1 LE Elbit Systems Ltd. Israel 2,9 2,2 Table 1: List of evaluated UAVs and their base dimensions

M


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Next step is to define wanted configuration of designed aircraft. Forward looking camera means that the view must remain unobscured. Furthermore there is a requirement that the design should be unconventional. As a result, canard configuration with pushing propeller will be used.

A big deal of time have been spent by selecting proper airfoil for wing and canard and overall dimensions. A total of 43 different configurations have been evaluated. Table 2 shows some of the configurations evaluated. Software XFLR, AVL and XFOIL, all three based on panel methods, were used as a main aerodynamic optimization tool. Many different low Reynolds number optimized Eppler airfoils, as well as some NACA and GA(W) airfoils have been evaluated. At the end airfoils E205 for the wing and E214 for the canard have been selected and further developed (vertical position, sweep angle, taper ratio etc.)

Configuration Wing airfoil Canard Airfoil

Wing area [m2]

Canard area [m2] α [°] δ [°] vmin [m/s]

1 E214 E214 0,5 0,072 0,19 10

2 E214 E214 0,5 0,072 0,19 9,95

3 NACA 4415 E214 0,5 0,072 1,65 7

4 NACA 4415 E214 0,5 0,084 1,54 5,6 9,5

5 E205 E214 0,5 0,084 3,2 2,15 10,85

6 E374 E214 0,5 0,084 3,8 1,3 11,3

7 E387 E214 0,5 0,084 2,1 4,2 10,2

8 E387 E205 0,5 0,084 2,25 5,72 10,2

9 E387 NACA 4415 0,5 0,084 2,17 4,7 10,2

10 E205 E210 0,5 0,084 3,32 3,64 10,68

11 E205 NACA 4415 0,5 0,084 3,26 2,6 10,65

12 GA(W)-2 E214 0,5 0,084 1,36 6,49 9,53

13 FX-63-137 E214 0,5 0,084 -2,59 14 8,47

14 E387 FX 63-137 0,5 0,084 3,32 3,74 10,68

15 E210 FX 63-137 0,5 0,084 0,3 6,35 9,49 Table 2: List of some configurations evaluated

Not only different airfoils but also vertical position of wing and canard have been evaluated. Figure 2 shows final vertical configuration used and interaction of canard disturbed airflow and the wing.

Figure 1: Canard - wing configuration and flow visualization, 3° Angle of Attack

Figure 2 shows final design of the aircraft. Figure 3 shows final dimensions. As the whole aircraft is designed with minimum price and maximal simplicity in mind, it has been determined that the main material to be used is wood. Bulkheads, bottom part and internal balance box are made of 4 mm plywood. Fuselage is made of 1 mm balsa wood. Some other parts, such as canard-fuselage transition are to be 3D printed of ABS plastic. Further development of the aircraft may lead to use of composite materials.


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Figure 2: UAV final design Figure 3: Final design with dimensions

III. Aircraft Performance There are no certification specification regulations in the Czech Republic that would deal with UAVs with

MTOW less than 20 kg. For v-n diagram UL-2 specifications were used. As no aerobatic maneuvers are expected, maximum load factor used for wing spar design is set to 4. Figure 4 shows v-n diagram.

Although the aircraft will be capable of high speed flight (around 100 kph), design cruising airspeed is lower (around 50 kph) – endurance is the primary goal of the aircraft. Figure 5 shows power required (red line) and power available (blue lines) of different 11” propellers. These data are theoretical and real data are subject to wind tunnel testing.

Figure 4: v-n diagramm


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Figure 5: Power required and power available

IV. Power Subsystem Design Suitable power system has to been designed for this aircraft. The decission has been made by criteria like mass

of the aircraft, expected number of battery cells, mass of its own engine, efficiency of the engine etc. Expected parameters:

• Mass of the aircraft: up to 4kg • Number of battery cells: 5 • Battery: 2x FOXY G2 Li-Pol 5000mAh/18.5V 36/70C - [1]

In the selection of the engine has been considered opinion of Petr Adámek, who designed the airframe and added

graphs of required thrust and power as is shown in Figure 6. These graphs are for 8000rpm and for propeller 11x7.

Figure 6: Power required and Thrust required

Chosen engine:

• Type: AXI 4120/14 GOLD LINE


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• Specification: Technical specifications can be found in [2] • Description: This electric engine is suitable for model of gliders, which our airframe in fact is, up to

mass 4.5kg. • Chosen controller: On the manufacturer’s recommendations, JETI spin 66 [3] controller is chosen. The

controller includes BEC safety circuit which is advantageous. Next step in power subsystem design is battery. As is described in article [4], best way between reaching longest

flight time and total weight is to choose batteries that weigh from 61% to 87% of airframe without batteries. The best compromise is when batteries weigh 83% of airframe as is shown in Figure 8.

Figure 8: Relative changes in flight time, total airframe weight and difference between the reductions.

From that and financial reasons two batteries described above was chosen. Both of them weigh 1.268kg. Airframe itself weighs 2kg it responds 63% of airframe.

V. Mathematical Model Mathematical model is built in Simulink in which Aerospace toolbox [5] has been used. In order to determine behaviour of the aircraft, various coefficients have to be known. These include coefficients

of lift, drag, various pitching, rolling and yawing derivatives and steady flight deflection angles of moving surfaces (e.g. ailerons, canards and rudder). Although wind tunnel testing of the prototype would bring the best results, it is necessary to know such coefficients even before the prototype is built. One of the methods that can be used is again panel method. In this particular case program AVL by Mark Drela from MIT is being used. Geometry is imported from XFLR and mass values, including position if center of gravity from 3D model.

Coefficients values were obtained as follows. The speed is set up to a specific value and range of angles of attack

is specified. The aircraft can be evaluated both with fixed moving surface or unfixed, under the condition that pitching, rolling and yawing moments stay at specific value. This allows knowing deflection angle of the canard needed for steady level flight at any given speed (or angle of attack).

Based on knowing coefficients we determined following equations. Equations (2), (4) and(6) are created for steady flight when parameters are: air speed – 15 m/s angle of attack – 3.78°

CD =CDa4*a4 + CDa3*a

3 + CDa2*a

2+ CDa1*a1 + CDa0 (1)

This equation describes drag coefficient of wings and fuselage. It is created by fitting a fourth order polynomial as is shown in Figure 9.


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Figure 9: Process of the drag coefficient and replacing by a fourth order polynomial

Cy = CYb*b + CYp*p*b_ref/(2*V) + CYr*r*b_ref/(2*V) + CYdr*dr (2)

CL = CLa*a+CLa0 + C.CLq*q*C.d_ref/(2*V)+C.CLde*de (3)

This equation is created by fitting linear line as is shown in Figure 10.

Figure 10: CL depends on angle of attack

The linearity error is shown in Figure 11.


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Figure 11: Linearity error

Cl = Clb*b + Clp*p*b_ref/(2*V) + Clr*r*b_ref/(2*V) + Clda*da + Cldr*dr (4)

Cm = (Cma*a + Cma0) + Cmq*q*d_ref/(2*V) + Cmde*de (5) This equation is created by fitting linear line as is shown in Figure 12.

Figure 12: Cm depends on angle of attack

The linearity error is shown in Figure 13.


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Figure 13: Linearity error

Cn = Cnb*b + Cnp*p*b_ref/(2*V) + Cnr*r*b_ref/(2*V) + Cnda*da + Cndr*dr (6)

VI. Flight Control Unit Requirements The main goal of the FCU system we have been developing is to build control unit which can be used with

designed aircraft and its particular components. These componets are mainly based on RC model subsystems. Thus it is necessary to substitute the original RC transmitter and reciever system with more suitable communication channel. The minimal required range of this wireless communication system is 1 mile. Other requirements follow from expected functions of autonomous control algorithms, primarily attitude and heading reference system, localization system, measuring of airspeed, barometric altitude, angle of attack and other flight parameters. The system should be capable of implementation of complex control laws and sensor fusion algorithms such as Kalman Filter for AHRS and LQ or other MIMO feedback loops for stabilization, navigation or formation control.

Last group of requierements respects the potential higher-level algorithms which are expected to be developed on top of the control unit – wind estimation, variometer, distance measuring or estimation of relative position in a formation. The important feature in this category is also high data rate capability of communication channel which can be used by multiple vehicles in formation or for large datasets transfering.

Additional requirements ar related to Ground Control Station (GCS). Main purpose of GCS is real-time control of vehicle in manual mode or command forwarding in one of the autonomous regimes. These commands can be set through the basic user interface on GCS, or can be forwarded from personal computer or from mobile device with Android OS. The basic flight parameters should be shown on the GCS.

VII. Flight Control Unit Specifications The specifications of the whole system and selected subsystems respecting the requirements described above

section are detailed in this section.

A. Main Processor The microcontroller used in the flight control unit should be capable of reading all values from sensors with

different interfaces including analog outputs, I2C, SPI buses, or serial communication. It should have capability of computing complex algorithms for AHRS or feedback loops. For this project the 32 bit ARM controller STM32F100RB was choosen. The advantage is that it has the same pinout as higher versions of controllers from STM, which means that more powerfull processor can be used with the same PCB if necessary.


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B. Communication Channel The first functionality which has to be

solved is communication. In this project the commercialy available x-bee modules have been selected. The main reason is that the development of new communication channel from scratch overlaps the magnitude of this project and it can be done in the future if necessary. The advantage of x-bee (or the modules implements Zigbee protocol) is that there are more variants of specific version which differ in frequencies, output power, coverage, data rates, but all have the same interface for connecting to master device. Another significant advantage of communication modules based on Zigbee protocol is the native support of multi-point networking, which can be useful in formation control projects. Disadvantage of this solution is non zero latency of communication channel but the latency is still small enought to provide real time manual control. The Zigbee modems used in this project are XBee Pro 50mW Series 2.5, one configured as Coordinator used in GCS and another in flier control unit configured as Routers.

Another option for communication channel is a GSM/GPRS modem which can provide connection for higher distances. The usability of this system is dependent on GSM signal coverage in particular area. The disadvantage of this option is latency, which is not determined and thus it is not possible to control the vehicle in manual mode. This communication channel can be used for transfering commands for autonomous mode of flight or to transfer larger datasets which are not real-time dependent such as video stream.

C. AHRS Unit For the attitude and heading reference system a full inertial measurement unit is used which includes 3 axes

gyro, accelerometer and magnetometer. This IMU is based on MEMS sensors, which are cheap and small, and precise enough for this application. Two versions of the IMU unit was used in this work – one based on MPU6050 chip integrates 3x gyro and 3x accelerometer with HMC5883L magnetometer, and second version based on LSM330 and the same magnetometer. These two versions are equivalent for this project, because DMP unit in MPU6050 is not used and all calculations for AHRS algorithm are processed in the main processor.

D. GPS and other sensors The main sensor used for localization and navigation is GPS reciever, in this project the GPS unit based on

MediaTek MT3329. This GPS unit provides 10 Hz sampling frequency. Another important flight parameters to be measured are barometrical height and airspeed. These values are measured with pressure sensors MPX4115A and MPXV7002DP.

E. Concept A solution based on one single communication channel. The main node of Ground Station System is a hardware

platform with basic user interface. This module has to be robust and reliable, but this approach makes the system independent on personal comupter and its malfunctions. The solution used in this work is shown on the block diagram on Fig. 14.

VIII. Onboard Hardware The onboard control system is divided into separate modules that are connected together and can be replaced or

upgraded. Main modules of the onboard system are processor unit with inertial measurement unit, GPS reciever, communication module and sensor boards. Prototypes of developed modules can be seen on Fig. 15.

Figure 14. Block scheme representing the overall concept and hierarchy of used control system.


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Main Processor Board is fitted with 32-bit microporcessor STM32F100RB. This mpc is based on ARM Cortex M3 core and the working frequency is 24 MHz. There are slots for communication module (xbee) on top side of the pcb, inertial measurement unit and data looger flash memory is included, and input/oputput ports located on this board. Inertial measurement unit is based on chips HMC5883L and LSM330. The input / output ports includes 8 PWM outputs for controlling servos, 3 USART lines for x-bee, logger and GPS, I2C for secondary inertial measurement unit or magneotmeter, 6 analog inputs, and GPIO pins for another use.

IX. Onboard Software This chapter describes the basic version of onboard software for all units which have been implemented in this

project so far. First, the values from sensors are collected and processed. The most important part of the software is computing the attidute estimate of the vehicle. The stabilization and control feedback loops can be than implemented. The last part which has to be implemented before flight experiments can be performed in real environment is the communication with GCS.

AHRS Software Precise and reliable estimation of orientation plays crucial role for unmanned vehicle. The most common solution to

determination of the three orientation angles: pitch, roll, and yaw, relies on the AHRS that exploits inertial data fusion (accelerations and angular rates) with magnetic measurements. However, in real world applications strong vibrations and disturbances in magnetic field usually cause this approach to provide poor results. Therefore, we have devised a new approach to orientation estimation using inertial sensors only. It is based on modified complementary filtering and was proved by precise laboratory testing using rotational tilt platform as well as by robot field-testing1. As it appears, the algorithm outperformes the commercial magnetometer-aided AHRS solutions.

The data fusion process can be described as follows (for the block scheme, see Fig. 16):

First, the calibrated accelerations and angular rates are pre-filtered – various filter types were investigated to deal best with the vibrations.

Second, the coarse alignment algorithm1-3 is applied on the inertial data to obtain pitch and roll angles. Then, the angular rate data are numerically integrated; quaternions are used for attitude representation to ensure smooth rotations and save computations when chaining the rotations (compared to rotation matrices approach).

Third, angles obtained from the coarse alignment and by the integration are fused together using specially designed complementary filter1.

Fourth, results of the data fusion are fed back to the angular rates channel to ensure stable solution and to minimize the error due to noise

Figure 15: Prototypes of developed modules.

Figure 16. Block scheme representing the principle of the orientation determination algorithm: a complementary filtering approach that uses inertial data only.[1]


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integration and drift. For more details of this method see Ref. [1].

Stabilization Algorithms The basic stabilization algorithms have

been implemented in this project. Block scheme of used stabilization feedback loops for lateral and longitudinal motion is on Fig. 17. The first loops are angular-rate dampers, the subsequent feedback loop implement simple P control of attitude angles stabilization. The system is capable of tuning the controllers gains indepentendly from ground control station.

X. Ground Station Hardware ground station was developed for communication with the unmanned aerial vehicle. This ground

station is designed to be the main node for interaction between the user, onboard control unit and software ground system running on computer or Android mobile device. One of the main tasks of the GCS is to replace the original transmitter of RC system and provide duplex communication channel with onboard control unit. The GCS must be robust and reliable, becouse it is the only way how to communicate with flying UAV. This is the reason why complex hardware ground station is used instead of only xbee-usb adaptor used in similar projects4-7. GCS is based on STM32F100RB processor, it is equipped with graphical display, set of trimmers and switches. GCS is equiped with 3x USART lines for x-beee module, bluetooth module and PC connection.

The picture of the Ground Station is on Figure 18. The ground station can be connected to visaluzation and control software running on a personal computer. The

basic version of this software has been developed in this project. This version is using Open Street Maps and is based on .NET platform and writen in C#. This basic version is capable to display the position of the vehicle on the map, the euler angles and other flight parameters. The GCS can be also connected to Android mobile device via Bluetooth. The pictures of developed aplication for personal computer and Android device is on Figure 19.

To make the system more compatible with other available systems, the MAVlink has been implemented. This means that our system is capable to communicate with MAVlink-based open source GCS software such as QGroundControl, HK Ground Control Station, APM Planner and some others.

Figure 18: Prototype of Ground Control System.

Figure 17. Block scheme representing stabilization algorithms.


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XI. Conclusion This paper describes the first phase of a students project of the autonomous Unmanned Aerial Vehicle. In this

first stage, the aircraft design and performances has been investigated, hardware platform for desired system was developed and tested with low-level software and fundamental AHRS and flight control algorithms. Basic mathematical model of dynamical behavior of designed aircraft has been derived. All HW subsystems including communication channel with MAVlink protocol, ground station, and the on-board electronics were designed and assembled, all program codes were written, debugged and tuned, and all the efforts resulted in first successful experimental flights of flight control units. These tests has been performed with different aircraft, while the designed platform is not ready for testing yet. The performed flight experiments prooved that the hw of flight control system is capable of autonomous driving of aerial vehicle and it comply with requirements and expectations.

Next phases of the project will cover implementing the higher control algorithms including LQ regulation based on derived mathematical model. After assembly of the designed aircraft platform final tests and measurements can be done.

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Robotics and Automation (ICRA), 2012 IEEE International Conference on , vol., no., pp.599-605, 14-18 May 2012 2M. Sotak, "Coarse alignment algorithm for ADIS16405," Przeglad Elektrotechniczny, vol. 86, no. 9, pp. 247-251, 9 2010. 3E.-H. Shin, Accuracy Improvement of Low Cost INS/GPS for Land Applications, M.S. thesis, Department of Geomatics

Engineering, University of Calgary, December 2001. 4https://pixhawk.ethz.ch/px4/modules/px4fmu 5Lorenz Meier, Petri Tanskanen, Lionel Heng, Gim Hee Lee, Friedrich Fraundorfer, and Marc Pollefeys. Pixhawk: A micro

aerial vehicle design for autonomous flight using onboard computer vision. Autonomous Robots (AURO), 2012. 6http://code.google.com/p/ardupilot-mega/wiki/Introduction 7http://www.openpilot.org/products/openpilot-Revolution-platform/ 8http://qgroundcontrol.org/mavlink/start 9Datasheet STM32F100 [online]. 2012 [cit. 2012-05-19]. http://www.farnell.com/datasheets/1393655.pdf 10Datasheet HMC5883L [online]. 2012 [cit. 2012-05-19].

http://www.honeywell.com/sites/servlet/com.merx.npoint.servlets.DocumentServlet?docid=DCB000D72-C325-A8BE-588A-322B3EC915DE

11Kortunov V., Dybska I., Proskura G. and Kravchuk A. “Integrated mini INS/GPS/Optical camera for UAV control”, Symposium gyro technology 2008. - Karlsruhe, Germany, 16-17 September, 2008. - P.12.1-12.8. 11

Figure 19. Screenshot of GCS software for PC (a), or for Android device (b).


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12E.-H. Shin, Estimation Techniques for Low-Cost Inertial Navigation, Ph.D. dissertation, Department of Geomatics Engineering, University of Calgary, 2005.

13KUNDU, Ajoy Kumar. Aircraft design. New York: Cambridge University Press, 2010, xlii, 606 p. ISBN 978-052-1885-164.

14RAYMER, Daniel P. Aircraft design: a conceptual approach. Washington, D.C.: American Institute of Aeronautics and Astronautics, c1989, 729 p., [1] p. of plates. ISBN 09-304-0351-7.

15SELIG, Michael S. Summary of low speed airfoil data: a conceptual approach. Virginia Beach, Va.: SoarTech Publications, c1995-, v. <1 >. ISBN 09-646-7471-8.

16SELIG, Michael S. Airfoils at Low Speeds. Virginia Beach: H. A. Stokely, publisher, 1989. 408 s. 17Unmanned Vehicles Handbook 2008. Bucks: The Shepard Press Ltd., 2007. ISSN 1365-6546.

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