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Session B9: Complementary PNT: Vision Aided/Optical Ground

Restricting Inertial Navigation System Position Error Growth Using High Accuracy Vehicle Velocity Vectors
Stephen Sandford, Jason Hull, Diego Pierrottet, Jeff Monaco, Jon Ward, Corin Sandford, Phil Works, Brian Devey, Connor Huffine, Brendan Smith, Mark Christman, Donald Erbschloe
Location: Ballroom B
Alternate Number 2

Objectives: The goal of this effort is to overcome vulnerabilities of current navigation systems to unreliable GPS signal reception. When GPS signals are not available or reception is sporadic, the backup is typically an Inertial Navigation System (INS). The INS estimates navigation states until a new absolute location fix is obtained. A critical component is the Inertial Measurement Unit (IMU), a combination of accelerometers and gyroscopes to measure rotations and accelerations. IMUs are available in several grades, di?erentiated by the degree of precision required to perform the primary function of the unit—in general, the greater the precision, the greater the cost. Currently, affordable IMUs have very short useful operational durations, largely due to integration errors from the inertial sensors. Psionic employs a multi-beam Doppler Lidar approach to remedy these errors. The Psionic Inertial Navigation System is built on non-RF sensing technologies that support positioning requirements in degraded and unreliable environments. The system is derived from technology developed for space applications. The Psionic solution targets terrestrial use-cases. Near term work is focused on ground vehicle navigation and autonomous vehicle use. The system is designed for 6 degrees of freedom operations, and future objectives include aerial vehicle navigation for manned and unmanned applications.
Anticipated or Actual Results: Multiple units were built and used for ground demonstrations in various terrain environments. We also supported testing and documented results on a variety of test courses. The test runs involved travel over a variety of ground surfaces from pavement, hard and soft-packed dirt, vegetation, and snow. Simulations were also designed and employed and provided important insights into the performance of the INS, as well as confirming the impacts of various design changes in both hardware and software. Important improvements include a reduction in size, weight, and power through architecture modification. We anticipated and demonstrated reliable and repeatable improvement in navigation performance. Specific results from recent test events will be briefed.
Conclusions: The development work included system dynamic models, Monte-Carlo simulation of several hundred virtual road tests, and the actual hardware and software build, integration, and testing. The simulations offered important insights into the performance of the INS and confirmed various design changes in both hardware and software. Important improvements include a reduction in size, weight, and power and the use of an improved inertial measurement unit and state estimation. The system model enabled testing of the navigation filter and accelerated progress by allowing efficient assessment of proposed improvements. The enhanced INS has demonstrated better or comparable performance to high grade INSs at reduced cost . The Psionic system reduces the need for additional sensing capabilities to be integrated into the system. This makes high performance navigation significantly less expensive than current systems.
Significance of Psionic’s Work: When GPS signals are absent or compromised, inertial navigation systems become critically important. Current INS technologies degrade over time due to the integration of small errors in IMU accelerometers and angular rate sensors. Specifically, position error tends to grow exponentially with time. Psionic addresses and remedies these by adding complementary sensor information to reduce overall positioning errors.

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