Evaluation of a Geiger-mode imaging flash lidar in the approach phase for autonomous safe landing on the Moon

The imaging flash lidar has been considered as a promising sensor for the future space missions such as autonomous safe landing, spacecraft rendezvous and docking due to its ability to provide a full 3D scene with a single or multiple laser pulses. The linear-mode flash lidar has been developed and demonstrated for an autonomous safe landing on the Moon in order to provide an accurate distance measurement to the landing site and its 3D image. Yet, the Geiger-mode flash lidar has also been recognized as an emerging technology for the space missions because it is highly sensitive even to a single photon and provides the very accurate timing of photon arrival. In this study, the performance of the Geiger-mode flash lidar is simulated in the approach phase and evaluated for the autonomous landing on the Moon. Furthermore, a new statistical signal processing algorithm is proposed to remove the noise counts in order to obtain the 3D image from a sequence of laser pulses in the situation of the fast moving spacecraft. The algorithm is shown to be effective for the autonomous landing due to its ability to remove noise events under the condition of low signal-to-noise ratio and improve ranging accuracy.     

Adaptive Two-Stage Extended Kalman Filter for a Fault-Tolerant INS-GPS Loosely Coupled System

The well-known conventional Kalman filter requires an accurate system model and exact stochastic information. But in a number of situations, the system model has an unknown bias, which may degrade the performance of the Kalman filter or may cause the filter to diverge. The effect of the unknown bias may be more pronounced on the extended Kalman filter (EKF), which is a nonlinear filter. The two-stage extended Kalman filter (TEKF) with respect to this problem has been receiving considerable attention for a long time. Recently, the optimal two-stage Kalman filter (TKF) for linear stochastic systems with a constant bias or a random bias has been proposed by several researchers. A TEKF can also be similarly derived as the optimal TKF. In the case of a random bias, the TEKF assumes that the information of a random bi?s is known. But the information of a random bias is unknown or partially known in general. To solve this problem, this paper proposes an adaptive two-stage extended Kalman filter (ATEKF) using an adaptive fading EKF. To verify the performance of the proposed ATEKF, the ATEKF is applied to the INS-GPS (inertial navigation system-Global Positioning System) loosely coupled system with an unknown fault bias. The proposed ATEKF tracked/estimated the unknown bias effectively although the information about the random bias was unknown.     

Simultaneous spacecraft attitude and orbit estimation using magnetic field vector measurements

Based on magnetometer measurements only, three-axis attitude, rate, and orbit estimation are successfully achieved. A single Augmented Dynamics Extended Kalman Filter (ADEKF) is configured by combining the spacecraft nonlinear attitude dynamics and quaternion kinematics with orbital mechanics. The filter design is adopted for three-axis stabilized spacecraft in low Earth orbits where the aerodynamic drag is the dominant source of disturbances in addition to the spacecraft magnetic residuals. To reduce the computational burden, another Interlaced Extended Kalman Filter (IEKF) is developed to uncouple the attitude/rate from the orbit dynamics. Both filters are implemented using the magnetometer measurements and their corresponding time derivatives. As a part of EgyptSat-1 flight scenario, detumbling and standby modes are used for performance testing of the ADEKF. The concept of local observability is applied to the basic filter and the stability is investigated by incorporating extensive Monte Carlo simulations with uniformly distributed initial conditions. The filter shows the capability of estimating the attitude better than 5 deg and rate of order 0.03 deg/s in each axis. In orbit estimation, the filter is capable of estimating the position with accuracy less than 8 km and velocity upto 5 m/s in each axis.     

Preliminary results from the second flight of CREAM

Launched from McMurdo (Antarctica) in December 2005, the balloon experiment CREAM (cosmic ray energetics and mass) collected about 15 million triggers during its second flight of 28 days. Redundant charge identification, by two pixelated silicon arrays and a time resolved pulse shaping technique from a scintillator system, allowed a clear signature of the primary nuclei. The energy was measured with a tungsten/SciFi calorimeter preceded by a graphite target. Preliminary results from the analysis of the data of the second flight are presented.     

Sensitivity analysis of test methods for aspheric off-axis mirrors

Following the Hubble Space Telescope (HST), the next generation James Webb Space Telescope (JWST) is being developed to be launched in a few years. JWST will be a segmented mirror telescope with a design much like that developed for ground-based telescopes over the past 20 years. Several segmented mirror telescopes are currently in operation, and next generation ground-based telescopes of the 30-m class are also being designed using segmented primary mirrors. Regardless of size, segmented primary mirror telescopes often require the use of aspheric segment mirrors. One of the key factors in fabrication of aspheric segment mirrors is feasibility of testing off-axis surfaces with high accuracy. A couple of test methods have been investigated for aspheric off-axis segments. As a case study, we apply these test methods to secondary segmented mirror models of the Giant Magellan Telescope. We derive required dimensions of test set-ups and assess sensitivity of optical alignment. Characteristics of the test methods are also discussed.     

Stability analysis of explicit guidance laws for space launch vehicles with varying thrust integrals

In this study, a stability analysis of the explicit guidance laws for space launch vehicles is performed with consideration of varying thrust integrals. Among various forms of explicit guidance, linear tangent guidance in its general form is selected and six different acceleration profiles are considered for this numerical experiment. A linear system modeling which includes all of the significant dynamic elements of a space launcher is performed to analyze the effect of the characteristics of thrust integrals on stability margins. Numerical results show that in an aspect of guidance stability, it is advantageous to have thrust integrals derived from increasing acceleration profiles, such as constant thrust case, which may be considered in the development of propulsion systems. Finally, time-domain simulation with the original nonlinear models is performed to verify the approach and the result shows that the nonlinear dynamics of the system is conserved well in the linear model.     

Equivalent ARMA model representation for RLG random errors

It is shown that a mixture of random noises can be represented by a single equivalent ARMA (autoregressive moving average) model that is simple to implement. We applied the scheme to model RLG (ring laser gyroscope) random errors. An identification result from real test data confirms the validity of this approach     

Stochastic structural optimization using particle swarm optimization, surrogate models and Bayesian statistics

This paper focuses on a method to solve structural optimization problems using particle swarm optimization (PSO), surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method (RSM) and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.     

Ionospheric anomalies observed over South Korea preceding the Great Tohoku earthquake of 2011

We investigated the ionospheric anomalies observed before the Tohoku earthquake, which occurred near the northeast coast of Honshu, Japan on 11 March, 2011. Based on data from a ground-based Global Positioning System (GPS) network on the Korean Peninsula, ionospheric anomalies were detected in the total electron content (TEC) during the daytime a few days before earthquake. Ionospheric TEC anomalies appeared on 5, 8 and 11 March. In particular, the ionospheric disturbances on 8 March evidenced a remarkable increase in TEC. The GPS TEC variation associated with the Tohoku earthquake was an increase of approximately 20 total electron content units (TECU), observed simultaneously in local and global TEC measurements. To investigate these pre-earthquake ionospheric anomalies, space weather conditions such as the solar activity index (F10.7) and geomagnetic activity indices (the Kp and Dst indices) were examined. We also created two-dimensional TEC maps to visual the spatial variations in the ionospheric anomalies preceding the earthquake.     

Modeling quaternion errors in SDINS: computer frame approach

We propose new equivalent tilt error models which are applicable to the analysis of the terrestrial strapdown inertial navigation systems (SDINS), based on the quaternions. The currently available equivalent tilt error models, like the conventional Φ model of the gimbaled inertial navigation systems (GINS), are derived only by the true frame approach. The true frame approach has a computational disadvantage that it produces an error model where the attitude error equation is coupled with its position and velocity error equations. The motivation of this work is to solve this problem. As a result, two kinds of error models are derived. Among them, one is derived by the computer frame approach for practical onboard implementations. Thus, like the conventional GINS Ψ model, its attitude error equation is decoupled from the position and velocity error equations. The other is derived in order to show the relationship between the true frame approach and the computer frame approach which are applied to the quaternion-based SDINS. Thus, like the GINS δΘ model, it can be used to transform the error variables into each other which are calculated by the two different approaches