Article Figures & Data
Figures
- FIGURE 1
ARMAS framework state diagram (Jurado & Raquet, 2019): A sensor begins at point O (origin) and is trusted or untrusted. SAARM and the new contribution SOM reside within the Monitoring (M) Mode.
- FIGURE 2
SAARM T-matrix for i = 1…I all-source sensors (Jurado et al., 2020b)
- FIGURE 3
sUAS flight test data from October 12, 2018, at Camp Atterbury, Indiana
- FIGURE 4
Trace of a-posteriori Layer 1 subfilter position covariance simulated single GPS 15 pseudorange sensor failure
- FIGURE 5
Trace of a-posteriori Layer 2 subfilter position covariance simulated single GPS 15 pseudorange sensor failure
- FIGURE 6
ARMAS framework with novel observability layer for resiliency to one simultaneous sensor failure
- FIGURE 7
Sample of 10-SV stationary constellation skyplot with discrete random uniform elevations and one satellite directly overhead
- FIGURE 8
300 runs of sample truth trajectories
- FIGURE 9
Scenario 1 state estimation error for one run with a sensor anomaly from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 10
Scenario 1 mean 3D RSS error ± 1-σ for 1,000 runs with a sensor anomaly from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 12
Scenario 2 Mean 3D RSS error ± 1-σ for 1,000 runs with a sensor linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 11
Scenario 2 state estimation error for one run with a linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 13
Scenario 3 state estimation error for one run with a sensor linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 14
Scenario 3 mean 3D RSS error ± 1-σ for 1,000 runs with a sensor linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 15
Scenario 4 state estimation error for one run with a sensor linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
- FIGURE 16
Scenario 4 mean 3D RSS error ± 1-σ for 1,000 runs with a sensor linear pseudorange ramp bias from t = 240 to 330 sec and a biased sensor added at t = 360 sec
Tables
- TABLE 1
Scenario 1 Results: RSS Error, GPS4 Exclusion Magnitude, Detection Rate, and Quantity of Augmented Sensors
4 Trusted SVs, 1000 Trials Algorithm Grand mean RSS error [m] (Median) Standard deviation [m] Mean GPS4 anomaly magnitude at exclusion [m] Detection rate for 40-meter bias Mean total added sensors EKF 916.0 (76.53) 1, 720.8 - - - ARMAS 694.3 (76.52) 684.3 44.53 0.01 - SOM 16.78 (10.15) 18.25 41.51 0.99 3.00 - TABLE 2
Scenario 2 Results: RSS Error, GPS4 Exclusion Magnitude, Detection Rate, and Quantity of Augmented Sensors
5 Trusted SVs, 1000 Trials Algorithm Grand mean RSS error [m] (Median) Standard deviation [m] Mean GPS4 anomaly magnitude at exclusion [m] Detection rate for 40-meter bias Mean total added sensors EKF 283.5 (36.42) 411.3 – – – ARMAS 39.07 (22.44) 34.22 40.36 0.58 - SOM 12.14 (9.48) 7.25 37.93 1.00 2.00 - TABLE 3
Scenario 3 Results: RSS Error, GPS4 Exclusion Magnitude, Detection Rate, and Quantity of Augmented Sensors
6 Trusted SVs, 1000 Trials Algorithm Grand mean RSS error [m] (Median) Standard deviation [m] Mean GPS4 anomaly magnitude at exclusion [m] Detection rate for 40-meter bias Mean total added sensors EKF 153.7 (25.11) 213.6 – – – ARMAS 17.73 (12.94) 9.00 38.44 0.85 – SOM 12.34 (11.76) 3.97 38.44 1.00 1.00 - TABLE 4
Scenario 4 Results: RSS Error, GPS4 Exclusion Magnitude, Detection Rate, and Quantity of Augmented Sensors
7 Trusted SVs, 1000 Trials Algorithm Grand mean RSS error [m] (Median) Standard deviation [m] Mean GPS4 anomaly magnitude at exclusion [m] Detection rate for 40-meter bias Mean total added sensors EKF 85.52 (20.5) 113.4 – – – ARMAS 11.04 (10.08) 2.55 36.75 0.99 – SOM 11.04 (10.08) 2.55 36.75 0.99 0.00
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