1. AIRCRAFTS/HELICOPTER/UAV
OPTIMIZED INERTIAL NAVIGATION SYSTEM AND DNN FOR
AIRCRAFTS/HELICOPTER/UAV

2. PRESENTER INFORMATION
Name S.VARUN KUMAR
Year & Dept Third year, B.E Instrumentation and Controls
College St. Joseph’s college of engineering, Chennai
Address /28 Meeran Sahib Street,
Anna Salai, Chennai ID
Contact
LinkedIn profile
Ever since I could remember, I have had only one goal, which is to be a researcher. It was evident that the fascination and curiosity to know how technology could influence and drive our lives in many ways sparked my interest in the building new things. As a Junior majoring in Instrumentation and Control my ultimate career goal is to carry out research in the field of instrumentation and intelligent automation system.
Dream, Dream Dream Dreams transform into thoughts And thoughts result in action
- A.P.J. Abdul Kalam

3. PROBLEM STATEMENT
Design a system which would ensure high navigation solution integrity even in an environment with poor or no GPS/Satellite navigation signal. The system can either be an independent sensor or may make use of existing self-contained systems
DENSE FORESTRY MOUNTAINOUS REGIONS ROUGH DESERTS

4. IMPORTANCE OF THE PROPOSED PROJECT IN THE CONTEXT OF CURRENT STATUS
Between 2013 and mid-2016, there were nearly 80 incidents of aircraft GPS signal interference or malfunctions according to those filed on NASA’s Aviation Safety Reporting System (ASRS).
Pilots flying aircraft ranging from Cessna 172s to Airbus A300s have been reporting these incidents — and the incidents are not limited to the U.S. Other more high-profile incidents around the globe also highlight the problem
The vast majority of incidents involve GPS-based navigation systems either experiencing a total loss of signal or more alarmingly misreporting the aircraft’s position. In around 50 cases, no immediate explanation is given f or the malfunction.
SOURCE: Guy Buesnel, PNT security technologist at Spirient Communications, a communications networks provider based in the U.K.

5. PROPOSED SOLUTION
An inertial navigation system (INS) or inertial measurement unit (IMU) is a navigation aid that uses a computer, motion sensors and rotation sensors to continuously calculate via dead reckoning the position, orientation, and velocity of a moving object without the need for external references.
The proposed system measures both linear accelerations given by its accelerometer and angular velocity changes from its gyroscope and earth’s magnetism by magnetometer (9DOF).
The initial position is provided by some outside system (in the case of this project, using a
Global Positioning System (GPS) receiver when it is available).
Using a Raspberry Pi microcomputer as the base system and an inertial navigation system can be
developed and operated.
Kalman Filtering with GPS and IMU data will be used to complete a “strap down solution” - a
closed-loop system which can self-correct for error.
Moreover incorporating DNN into the flight controller can further enhance the path trajectory and navigation system.
Through this design the aircraft will be able to navigate through treacherous forestry and
places where GPS tends to fail or is unavailable.

6. BLOCK DIAGRAM

7. SYSTEM DESIGN - HARDWARE
LSM9DS0 Inertial Measurement Unit
SkyTraq Venus
634FLPx GPS
BMP 280 Barometer
Raspberry Pi 3B
Entire proposed IMS hardware cost is within >INR 6000

8. STANDLONE HARDWARE
SOC Robotics

9. SETUP METHOD STRAPDOWN INERTIAL NAVIGATION SYSTEM
A strap down INS is mainly comprised of three accelerometers and gyroscopes attached to the
aircraft. Each accelerometer measures the motion of the aircraft in three directions of travel, while the three gyroscopes are used to obtain information about the direction the aircraft is facing. With
the information from these sensors, the heading, speed and position of the aircraft can be
computed.

10. KALMAN FILTERING FOR OPTIMIZED NAVIGATION
The Kalman filter is a set of mathematical equations that is based on dynamic model of system. These equations are used to make an estimate of the current state of a system and correct the estimation using any available sensor
measurements.

11. OPTIMIZED NAVIGATION DATA
Blue line: IMU system, Blue dots: GPS Signals, Red line: Kalman estimated trajectory.
Kalman Filter is used to integrate two systems when the state of the system follows continuous state
dynamics and the measurement of the second system is related to the estimates provided by the first
system.
The second system is used to correct the state estimates provided by the first system to yield an
increased accuracy in state estimation

12. DEEP NEURAL NETWORK BASED NAVIGATION SYSTEM
A trail perception technique based on Deep Neural Networks can be
formulated where a dataset of the features is provided for download which can be efficiently acquired and used to train and test the Deep Neural Network model of the aircraft

13. INSIGHTS OF DEEP NEURAL NETWORKS
Deep Neural networks are a set of algorithms modelled loosely after the human brain,
that are designed to recognize patterns. They interpret sensory data through a kind of
machine perception, labelling or clustering raw input. The patterns they recognize are
numerical, contained in vectors, into which all real-world data, be it images, sound, text or time series, must be translated
Major features of DNN are,
Classification
Clustering
Predictive analysis

14. TIME SCHEDULE OF PROJECT ACTIVITIES -TENTATIVE

15. MULTITUDE OF PRECISE NAVIGATION OPTIONS
Optimized IMU Based
Navigation
On Board GPS
Trained DNN
model based
navigation

16. CONCLUSION Let Us Join Together In Bringing Our Soldiers Safely Home
The given solution of OPTIMIZED INERTIAL NAVIGATION SYSTEM AND DNN FOR
AIRCRAFTS/HELICOPTER/UAV proposed an IMU providing essential data for navigation
Using Kalman filtering, it is possible to combine those sensor data to help mitigate any errors
within a single sensor to create a more reliable independent navigation system.
Combining barometer and z-axis acceleration data, it is possible to get a more reliable
estimate of altitude changes.
Combining GPS and X and Y axis accelerometer data, it is possible to get reliable
displacement estimate within a couple of meters of actual, real-world displacement.
Moreover incorporating DNN into the flight controller can further enhance the navigation system.
However, when GPS data is not available, such as in a heavily forested area, the system can rely
entirely on INS sensor data and the trained DNN model for X and Y displacement to accurately
determine the navigation route.
Let Us Join Together In Bringing Our Soldiers Safely Home

17. REFERENCES
D. Titterton and J. Weston, Strapdown Inertial Navigation Technology,2nd ed. Reston, VA: AIAA, 2005.
InvenSense. MPU-9150 Datasheet, 18 Sept Web. gyro/documents/PS-MPU-9150A-00v4_3.pdf.
Weiss and J. Rowberg. 9 Degrees of Freedom - MPU-9150 Breakout (2013), GitHubrepository.
K. Townsend. Adafruit Unified BMP085/BMP180 Driver (2013), GitHub repository.
G. Henderson. Gordon’s Projects - WiringPi (2011), Web.
Schmidt, G.T., Strapdown Inertial Systems - Theory and Applications, “AGARD Lecture Series, No. 95,1978.
Bar-Itzhack, I.Y., and Berman, N., \Control Theoretic Approach to Inertial Navigation Systems, “Journal of Guidance, Vol. 11, No. 3, 1988, pp
Grewal, M.S., and Andrews, A.P., Kalman Filtering: Theory and Practice usingMATLAB, John Wiley and Sons, New York, 2001.
Grewal, M.S., Weill, L.R., and Andrews, A.P., Global Positioning Systems, Inertial Navigation, and Integration, John Wiley and Sons, New York, 2001.
Barbour, Neil and Howell, William C. (2014). Inertial navigation system. In AccessScience. McGraw-Hill Education.
Eure, K. W., Quach, C. C., Vazquez, S. L., & Hill, B. L. (2013). An application of UAV altitude estimation using a low-cost inertial navigation system No. NASA/TM ). Hampton, Virginia: NASA.
Nitti, D. O., Bovenga , F., Chiaradia, M. T., Greco, M., & Pinelli, G. (2015). Feasibility of using synthetic aperture radar to aid UAV navigation. Sensors, 15(8) doi: /s
Rapoport, I., & Brandes, A. (2010). Analysis of sculling motion errors caused by sensor transfer function imperfections in strapdown inertial navigation systems. Paper presented at the Position Location and Navigation Symposium (PLANS), 2010 IEEE/ION, doi: /PLANS

18. “A country shall not be sized by brute military force but by the courage of its selfless soldiers” THANK YOU