How does GNSS/INS integration improve performance during partial signal loss?

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Multiple Choice

How does GNSS/INS integration improve performance during partial signal loss?

Explanation:
GNSS/INS integration keeps the inertial estimates honest by using GNSS updates to correct the accumulated drift in position, velocity, and attitude. When signals are partially lost, the estimator relies on the last reliable GNSS information to maintain a reasonable state and then propagates that state forward with the inertial measurements, creating holdover estimates that keep the trajectory continuous. The amount of drift that accumulates during the outage grows with time and depends on how accurate the sensor bias and noise models are, so the remaining error stays within the filter’s predicted bounds rather than skyrocketing. When GNSS becomes available again, periodic updates bring the estimate back toward the true state, reducing the accumulated error. This approach provides much better continuity and accuracy than relying on inertial data alone.

GNSS/INS integration keeps the inertial estimates honest by using GNSS updates to correct the accumulated drift in position, velocity, and attitude. When signals are partially lost, the estimator relies on the last reliable GNSS information to maintain a reasonable state and then propagates that state forward with the inertial measurements, creating holdover estimates that keep the trajectory continuous. The amount of drift that accumulates during the outage grows with time and depends on how accurate the sensor bias and noise models are, so the remaining error stays within the filter’s predicted bounds rather than skyrocketing. When GNSS becomes available again, periodic updates bring the estimate back toward the true state, reducing the accumulated error. This approach provides much better continuity and accuracy than relying on inertial data alone.

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