Development of a Frequency Response INS/GPS System Model Based on LSSA for Bridging GPS Outage
Bibliographic record
Abstract
The integration of Inertial Navigation System (INS) and Global Positioning System (GPS) architectures can be achieved through the use of many filters such as, an extended Kalman filter, an unscented Kalman filter, divided difference filter, and particle filter. The main objective of all the above filters is to provide accurate fusion of the data from GPS and INS to predict INS-only navigation solution during GPS outages. The prediction mode performance of all these filters is very poor with significant drift in the INS-only solution. Time domain approaches are traditionally used to improve the INS-only solution such as, neural network models. In this paper, a new frequency domain method is proposed in which the frequency band of interest can easily be selected and used in the modeling. To develop a frequency domain method for INS/GPS bridging model for GPS outages, the frequency response of the INS/GPS system must be investigated. The Least Squares Spectral Analysis (LSSA) and a parametric transfer function in the complex Z-plane are employed to develop the frequency response. The input to this system is the INS-only solution and the output is the INS/GPS integration solution. Then, the discrete inverse Z-transform of the parametric transfer function is applied to estimate the impulse response of the INS/GPS system. To examine the performance of the proposed approach, a kinematic dataset is collected in Hamilton Harbour onboard a hydrographic surveying vessel owned by the Canadian Hydrographic Service, Canada. The loosely coupled INS/GPS integration with unscented Kalman filter is developed to obtain an INS/GPS integrated navigation solution and an INS-only solution. Then, the INS/GPS and INS-only navigation solution are used to develop the impulse response of the INS/GPS system. It is shown that the developed impulse response can be used to detect and recover the long-term motion dynamics during GPS outages with about 80% dynamic recovery for longitude solution and 50% dynamic recovery for east velocity solution when compared with the INS-only solution (prediction mode of the INS/GPS filter).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".