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Development of Mine Detection System

This presentation discusses the development of a mine detection system mounted aboard a helicopter and the statistical analyses involved in that effort.

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Development of Mine Detection System

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  1. Development of Mine Detection System Jim Sellers Mechatronics Systems Engineering Consultant 8-10 December 2014 International Summit on Industrial Engineering San Francisco, CA USA

  2. Abstract Land mines have been used extensively in worldwide conflicts for many years, and have killed and maimed an untold number of warriors and civilians. These explosives remain buried long after the hostilities end and still wreak havoc on unsuspecting citizenry going about their normal lives. An international outcry regarding these dangers resulted in efforts to end their use and to rid known mined areas of these dangers. This presentation discusses the development of a mine detection system mounted aboard a helicopter and the statistical analyses involved in that effort.

  3. Introduction • Proof of concept program only. • Requirements are typical but not specific. • Helicopter-mounted turret laser scanner. • Want to scan certain area of ground with laser to assist in detecting mines. • Very politically-charged topic for many years.

  4. Typical Stabilized Turret

  5. System Operation • Dual-mode: coarse/vernier • Coarse: Two-axis gimbal provided by consultant. • Vernier: provided by azimuth and elevation fast steering mirrors (FSM) located on gimbal inner platform. • Combination of maximum specified helicopter height and detector array configuration yielded the conversion that one pixel size equals a certain distance of ground distance (83 microradian maximum subtended angle). • Sets total line-of-sight (LOS) pointing requirement. • As helicopter flies, combination of gimbal and FSMs produces raster scan utilizing Velocity/Altitude tracking to completely scan a certain area of ground in a repetitive stare-step-stare manner.

  6. System Operation • For raster scan, requirement was to align within one pixel at the beginning of each raster segment origin. •  Pointing accuracy requirement of 83 microradians. • During stare (dwell), one-half pixel size smear requirement was imposed. •  Pointing stability requirement was 41.5 microradians RMS. • Pointing stability requirement sets total LOS requirement.

  7. System Operation Analysis • Coarse turret provider specification: 16 microradian RMS pointing stability at the inner platform of the turret. •  LOS requirement imposed on combination of azimuth and elevation FSMs is 33 microradians RMS. • Looked for alternative approaches. • Showed by analysis that IF we could relax the helicopter forward velocity requirement by 15%, and IF we could use a slightly different ground coverage pattern, we could eliminate the elevation FSM entirely (even under worst-case crab angles).

  8. System Operation Analysis • Customer tentatively accepted this solution, meaning that azimuth FSM LOS pointing stability requirement is 33 urad RMS • Instead of V/H tracking-based raster scan, we now plan to use “broomsweep” pattern with flyback. • Since the azimuth FSM LOS experiences angular doubling, the azimuth FSM pointing stability requirement is 16.5 urad RMS. • Static error budget analysis and detailed Matlab/Simulink model was used to show that we could indeed meet this requirement with a very accurate absolute digital encoder as long as we could drop several of the encoder LSBs during flyback.

  9. System Test and Integration • Worked with mechanical, software, and electronics teammates to successfully build mirror, discretize control laws (including FSM bending mode compensation), and to bench test the azimuth FSM. • FSM worked correctly as predicted by my simulations. • End-item customer was very satisfied with proof-of-concept results.

  10. Summary • Carefully assess the requirements imposed on a system. Challenge when prudent to do so. • Ensure that analysis and simulation results make sense with regard to the physical limits of the real-world system. • Make sure that error analysis and subsequent budgeting are realistic. • Don’t “reinvent the wheel” if an existing similar system has done similar analyses, simulations, and testing. Leverage their work efforts and correlate if possible.

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