A new multipath channel estimation and mitigation using annihilation filter combined tracking loop implementation in software GPS receivers
Bibliographic record
Abstract
Abstract The multipath effect causes severe degradation in the positioning of commercial GPS receivers. Due to multipath error, the positioning accuracy could reach a few of 10 m. If the cumulative Multipath delay is less than 0.1–0.35 chips, then it is difficult to mitigate in GPS receivers. This causes severe degradation in GPS signals and can cause a measurement bias. To alleviate this problem, the estimation of multipath parameters using annihilating filter and its mitigation in the GPS tracking loop is proposed in this work. The estimation of randomly generated multipath signals can be performed in the receiver with a lower sampling rate when compared to the larger bandwidth of the GPS baseband signal. Here, the frequency components of the multipath signal in superimposed complex exponentials have been transformed from the time delay and the amplitude of the path observables. The Rayleigh fading model in the urban scenario has been simulated in which the amplitude and the phase of the number of paths (i.e. the frequency component of superimposed complex exponentials) are set and this fading signal is convolved with GPS signal that forms the multipath faded signal. In the GPS receiver post-processing stage, with the help of the annihilation filter, the multipath components are estimated, then an inverse/adaptive filter and compensation technique are further applied to mitigate the multipath component. The mean square error with the different number of paths with noisy environments is analyzed utilizing the cadzow denoising algorithm. The simulation results of the proposed technique employed in the tracking module of the software GPS receiver under severe multipath conditions indicate a substantial enhancement in the performance of the GPS receiver with minimal code and carrier phase error when compared to the least squares and adaptive blind equalization channel techniques. Moreover, the positioning accuracy is also calculated with the inclusion of multipath components in two satellites out of six satellites used in the simulation, the results showed that the annihilation filter improved the mean position accuracy up to 9.3023 m.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".