Inflight Alignment Simulation using Matlab Simulink

Transcription

1 Inflight Alignment Simulation using Matlab Simulink Authors, K. Chandana, Soumi Chakraborty, Saumya Shanker, R.S. Chandra Sekhar, G. Satheesh Reddy. RCI /DRDO The MathWorks, Inc. 1

2 Agenda with Challenging Issues as: How Weapons are Categorized What is an INS and why an INS is used How to align INS inflight Need for Inflight Alignment Bias Estimation during Maneuvring Need for Simulation Model Modules used in Simulation Testbed Simulation Test Results 2

3 Weapon come in types adapted for different purposes: Surface-to-Surface Air-to-Surface (ballistic, cruise, antiship, anti-tank) Surface-to-Air (anti-aircraft and antiballistic), Air-to-Air, and Anti-satellite Weapon. 3

4 Inertial Navigation System:INS Inertial navigation is the process of obtaining Position, Velocity and Attitude (PVA) by continuously integrating system acceleration and rotation rates measured by an orthogonal triad of accelerometers and gyroscope. How to align INS when its in motion? Methods to initialization Ground based Alignment In this method, initial velocity is taken to be zero without considering the environmental disturbances Initial position is provided by some external aiding such as GPS or surveyed positions. In Motion Alignment/Inflight Alignment In this case, as the system undergoes an arbitrary movement during initialization, it is not possible to assign initial values without an aid of some external reference source. 4

5 Inflight alignment In Brief In master/slave configurations, Master INS refers to the system which provides reference navigation values such as attitude, velocity, position. Slave INS refers to the system to be aligned and calibrated. Process of transfer of navigation information from a reference source to the navigation system when they are in arbitrary movement SINS is initialized with MINS Position Velocity Attitude Slave INS (INS in Weapon) MASTER INS Master INS (INS in Aircraft) SLAVE INS 5

6 Need for Inflight Alignment Alignment and initialization of INS in flight Estimate roll, pitch and azimuth in wing vibratory environment. Unaffordability of other forms of alignment Weapon INS:SINS Undergoing Wing Vibrations 6

7 Critical areas in Inflight Alignment Frame of navigation Gyro bias estimation Duration for alignment Specific Maneuver requirement Instant & Duration Of Maneuver Time Taken For Convergence x b Maneuvering y b z b MINS NED Frame 7

8 Inflight Alignment can be done using different techniques, one of the best possible way found to be Attitude Matching. Advantages of Attitude Matching Small accelerometer biases Minimal modeling errors MINS SINS No lever arm Ability to estimate gyro biases PVA How to Validate Attitude Matching Technique Attitude of the MINS is obtained along with the velocity information. In order to assess the effect of attitude measurements in estimation performance, a Kalman filter which uses only attitude information as measurement is constructed. The filter is thoroughly analyzed in simulation test bed. 8

9 Need for Simulation Model All the possible test conditions can be simulated and expected output can be seen. Easy flow of analyzing and understanding. Simulating the possible conditions which is not feasible in real time test environment. Real-time tests are done through van trials which would be difficult to test too many conditions having Petrol Hike. 9

10 Simulation test bed 6DOF Trajectory generator Induced errors Master INS PVA Slave INS Kalman Filter Misalignments and Gyro Bias estimates 10

11 Inflight Alignment Schematic ˆ M C S MINS Master Attitude Kalman Filter Slave Attitude b ib gyro bias estimates 11

12 KALMAN FILTER A nine state Kalman Filter is designed to find the estimates of attitude misalignment between MINS and SINS, and the sensor biases. X A X w k1 k k k z H X v k k k k The discrete observations on the process are related to the state via a linear transformation with usual nomenclature. STATE AND ITS DYNAMICS X X e ecef ie C b AX 3x 3 3x3 3x 3 3x3 0 3x 3 3x 3 03x 3 MEASUREMENT PROCESS Z C C C ecef S M obs S M ecef X MEASUREMENT RELATION TO STATE (MATRIX FORM) ecef S M Zobs I C S S( ) C MCecef MEASUREMENT RELATION TO STATE (VECTOR FORM) Zobs (2,3) ecef Zmeas Zobs (3,1) CS Zobs (1,2) 12

13 6DOF Model 1 In 1 2 In 2 3 In 3 4 In 4 5 In 5 6 In 6 7 In 7 Controls Winds RST Bank-angle to ailerons PI control States Sensors VelW Mach Ang Acc Euler AeroCoeff PropCoeff EngCoeff Mass ECEF MSL AGL REarth AConGnd Aerosonde UAV (Geodetic -frame EOM ) 1 states 4 Out 3 Ang Acc 6 Out 6 8 Out 8 10 Out Out 12 sensors 3 5 Out 5 7 Out Out 9 11 Out 11 mu R2D R2D STOP R2D mu Stop Simulation when A /C on the ground Airspeed Sideslip AOA Bank angle Pitch angle Heading -K- Bank-angle -to-aileron Proportional -K- 1 s Bank-angle -to-aileron Integral Bank angle Integrator Airspeed to elevator PID control Airspeed -to-elevator Proportional Airspeed -to-elevator Integral 1 s Airspeed error Integrator 25 Airspeed Command -K- -K- -K- Airspeed -to-elevator Derivative du /dt Airspeed error Derivative 13

14 MASTER INS MODULE 14

15 SLAVE INS MODULE 15

16 KALMAN OBSERVATION EXTRACTOR 16

17 KALMAN ESTIMATOR 17

18 SIMULATION TEST RESULTS Type/Time Of Maneuver Bias 10, 15, 20 deg/hr Pitch 18

19 Misalignment 1,1,1 Type/Time Of Maneuver Pitch 19

20 Bias 10, 15, 20 deg/hr Type/Time Of Maneuver S man@40sec 20

21 Misalignment 1,1,1 Type/Time Of Maneuver S man@40sec 21

22 Summary INS aligned inflight using Attitude Matching Technique, where misalignment estimated is found to be consistent. A Known Misalignment is fed and Kalman Filter estimated back to its correct value. Easy way of analyzing module to module parameter flow. Simulation testbed created using Matlab Simulink, Aerospace Toolbox. Thus this Testbed has brought out a clear vision of each module to examine. 22

23 REFERENCES 1 [Yuksel] YİĞİTER YÜKSEL, Design and Analysis of Inflight Alignment Algorithms, Middle East Technical University, [Ogata] K Ogata, Modern Control Engineering, Prentice Hall India, [Brown-Hwang] Brown & Hwang, Introduction to Random Signal Analysis and Applied Kalman filtering, Wiley, [Jazwinski] A Jazwinski, Stochastic Processes and Filtering Theory, Dover, [Shortelle] Shortelle K. J., Graham W. R.,F-16 Flight Tests of a Rapid Inflight Alignment Procedure, IEEE PLANS 1998, pp , [Spalding] Spalding K., An Efficient Rapid Inflight Alignment Filter, Proceedings of AIAA Guidance, Navigation and Control Conference, pp , [Stovall] Stovall S. H., Inflight Alignment, Naval Air Warfare Center Weapons Division, China Lake, [Rogers] Rogers R. M., Weapon IMU Inflight Alignment Using Aircraft Position from Actual Flight Tests, IEEE PLANS, pp , [Savage] Savage P. G., Strapdown System Algorithms, Advances in Strapdown Inertial Systems, NATO AGARD Lecture Series, No:133, [Titterton] Titterton D.H. and Weston J.L. Strapdown Inertial Navigation Technology, IEE Press, Peter Pergrinus Ltd., London,

24 THANK YOU 24