1. Use of FOS for Airborne Radar Target Detection of other Aircraft Example PDS Presentation for EEE 455 / 457 Preliminary Design Specification Presentation

2. Presentation Aim – Present Team Project to use a Fast Orthogonal Search algorithm to replace the Fast Fourier Transform algorithm in a fighter Radar for airborne Radar detection of other airborne targets – Obtain department approval to continue Presentation Motivation – Radar is a primary Air Force, Navy, and Army sensor – Assess that adequate preliminary design detail is present to proceed

3. Outline Background – The Current Situation – Existing System – Our Project Aim Scope Requirements Design Schedule Risks Summary Conclusion Questions

4. Intercept of Low Flying Target Mode Beam Pattern Pulse Pulsed Radar Range Return (Time Domain) Range Amplitude A Scope Display Target Ground Return P S D Frequency (GHz) f D Gnd f D Tgt Frequency f D Gnd f D Tgt Pulsed Doppler Frequency Spectrum Radar Receives Background Soft or Hardware Filter Bank

5. Antenna Power Duplexer Exciter Radar Data Processor Transmitter Receiver Rx Protection PW & PRF Display Beam Steering Control Background Common Pulsed Doppler Radar System Functional Block Diagram Layout Location of the commonly used FFT algorithm for target detection P ower Spectral Density Frequency (GHz) f D Gnd f D Tgt f D Gnd f D Tgt Fast Fourier Transform Filter Bank

6. Project Aim – Present the Team’s Preliminary Design of a Fast Orthogonal Search algorithm in a Pulsed Doppler fighter Radar for airborne Radar detection of other airborne targets instead of the FFT algorithm Project Motivation – Your reason for doing this if you want to state it – Radar is a primary Air Force, Navy, and Army sensor

7. Intercept of Low Flying Target Mode Beam Pattern Pulse Antenna Power Duplexer Exciter Radar Data Processor Transmitter Receiver Rx Protection PW & PRF Display Beam Steering Control Doppler Filtering in Airborne Radars and Our Project Most Common Implementation Software Filter Bank Fast Fourier Transform In RDP Our Proposed Implementation Software Filter Bank Fast Orthogonal Search Algorithm In RDP Filter Bank

8. Major Constraint –No Airborne Radar Available To Work On Alternative –Use Labvolt Radar Training System (LVRTS) –Similar Architecture and Pulsed Doppler Processing –Small enough to work on in Lab –We have one –Will adequately demonstrate the project principle and Design Antenna Power Duplexer Exciter Radar Data Processor Transmitter Receiver Rx Protection PW & PRF Display Beam Steering Control Scaling of Project Our Proposed Implementation Software Filter Bank Fast Orthogonal Search Algorithm In RDP

9. Use ECE Labvolt Radar Training System (LVRTS) Test with the LVRTS targets Not designing a tracking algorithm, just the filter and detection algorithm Project Scope

10. Requirements Main Functional Requirements 1.Be compatible with a modern software driven Canadian Military radar system 2.Use the same signal interface as the existing radar Performance Requirements 1.Detect same S/N targets 2.Maintain the same processing time as FFT from detection to display 3.Provide at least as good frequency resolution With the same or fewer samples than the existing FFT Limitations 1.Demonstrate on Labvolt 2.Software tool ABDA to program and run code before putting into radar 3.Lowest Cost Possible (limit $200)

11. 1553 databus msg to display Receiver Project Interface Requirements Radar Data Processor FFT Filter bank Heading Pitch Angle Bank Angle Air Speed Pulse Width PRF Range, Velocity, & Angle Tracking Amplitude Frequency Altitude Covariance Matrix Processor Data Stream Analog to Digital Converter FCS Avionics Range Sample Amplitude Frequency FOS Filter bank Interfaces: Inputs and Outputs Heading Pitch Angle Bank Angle Air Speed Altitude Data Stream Pulse Width PRF 1 st Level of Decomposition

12. Project Implementation Design Amplitude Frequency FOS Filter bank Interfaces: Inputs and Outputs Heading Pitch Angle Bank Angle Air Speed Altitude Data Stream Pulse Width PRF 2 nd Level of Decomposition Amplitude Frequency FOS Filter bank Data Stream Input Outputs Functional expansion of orthogonal functions Gram-Schmidt Orthogonalization algorithm Calculate the functional expansion weighting values Set Candidate Functions to be cos(wt) and sin(wt) Correlation of Data Stream with Functional Expansion Least Squares Error Calculation Error Threshold Comparison

13. Design Challenges 2 nd Level of Decomposition Amplitude Frequency FOS Filter bank Data Stream Input Outputs Functional expansion of orthogonal functions Gram-Schmidt Orthogonalization algorithm Calculate the functional expansion weighting values Set Candidate Functions to be cos(wt) and sin(wt) Correlation of Data Stream with Functional Expansion Least Squares Error Calculation Error Threshold Comparison

14. Work Break Down Research FOS process Find and Learn Graham Schmidt Orthogonalization Algorithm Design and build function generator Design and build an orthogonal function expansion module Design and build a correlater module Design and build a weighting function calculation module Design and build a least squares error calculation module Design and build an error threshold comparison module Assemble all the modules

15. Design Process Spiral Approach (Supervisor guided trial & error) –Believe we will need 3 iterations Primarily a software project –Suggested by supervisor as we have no experience Simulate in Matlab a FOS algorithm with simulation data Read the data stream digital parameters and make a FOS work Det. FOS and data parameters to meet min requirements Waterfall Approach (Supervisor guided trial & error) –Design and build the individual modules Testing –FOS vs requirements

16. Project Time Line FOS Filter bank Amplitude Frequency Interfaces: Inputs and Outputs Heading Pitch Angle Bank Angle Air Speed Altitude Data Stream Pulse Width PRF Work Break Down Structure Tasks are the lines

17. Risk Assessment Risks –No Parts required –Damage the Radar Receiver during implementation Mitigations –Simulations with MatLab Simulink –Company Support from Labvolt

18. Summary –Problem – Improve Radar Target Detection With FOS –Use LVRTS with same processing to emulate the airborne radar –Implement a FOS algorithm instead of an FFT –Main Requirement is “Replacement Fit” and same performance –Mixture Spiral and Waterfall Design Approach –Schedule –Risk Assessment

19. The Conclusion Problem –Improve Radar Detection With FOS Have a Plan and Design –Know the interfaces –Identified the Design Challenges Seeking Approval to Continue

20. Questions