In-situ resource utilization technologies for Mars life support systems.

The atmosphere of Mars has many of the ingredients that can be used to support human exploration missions. It can be "mined" and processed to produce oxygen, buffer gas, and water, resulting in significant savings on mission costs. The use of local materials, called ISRU (for in-situ resource utilization), is clearly an essential strategy for a long-term human presence on Mars from the standpoints of self-sufficiency, safety, and cost. Currently a substantial effort is underway by NASA to develop technologies and designs of chemical plants to make propellants from the Martian atmosphere. Consumables for life support, such as oxygen and water, will probably benefit greatly from this ISRU technology development for propellant production. However, the buffer gas needed to dilute oxygen for breathing is not a product of a propellant production plant. The buffer gas needs on each human Mars mission will probably be in the order of metric tons, primarily due to losses during airlock activity. Buffer gas can be separated, compressed, and purified from the Mars atmosphere. This paper discusses the buffer gas needs for a human mission to Mars and consider architectures for the generation of buffer gas including an option that integrates it to the propellant production plant.     

Assimilation of endmember variability in spectral mixture analysis for urban land cover extraction

Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class.     

An in situ laser induced breakdown spectroscope (LIBS) for Chandrayaan-2 rover: Ablation kinetics and emissivity estimations

A miniaturized in situ laser induced breakdown spectroscope-LIBS is one of the two lunar rover payloads to be flown in India’s next lunar mission Chandrayaan-2, with an objective to carry-out a precise qualitative and quantitative elemental analyses of lunar regolith at the proximity of the landing region. As per the imposed mission constraints and the executed design optimization studies, a compact and light-weight LIBS prototype model is developed at our premises. This paper mainly concerns with the estimation of theoretical aspects; especially on evaluation of elemental ablation parameters and signal-to-noise ratio (SNR) calculations for the designed instrument. Theoretical estimations and simulations yielded an incident laser power density of the order of 5 × 10¹⁰ W/cm² on the target surface at a defined lens-to-surface distance (LTSD) of 200 mm and revealed an SNR > 100 for most of the elements under consideration. This paper also addresses the impact of LTSD variation on detection capability. The estimation of plasma-temperatures was carried out utilizing the emission spectra obtained under high vacuum environments employing the LIBS laboratory model. Experimental investigations and the performed theoretical estimations asserted the successful operation of the configured LIBS instrument for in situ elemental analyses on lunar surface.     

Comparison of motion and stereo methods in passive ranging systems

The authors compare the estimates in passive ranging systems using motion and stereo approaches. It is shown that an integrated approach is necessary to provide better range estimates over a field-of-view (FOV) of interest in helicopter flight. The recursive approach for processing a sequence of stereo images, described together with a recursive motion algorithm (RMA), provides the basis for an integrated method to provide more accurate range information. Results based on motion sequences of stereo images are presented     

A statistical study of solar radio Type III bursts and space weather implication

Solar radio bursts (SRBs) are the signatures of various phenomenon that happen in the solar corona and interplanetary medium (IPM). In this article, we have studied occurrence of Type III bursts and their association with the Sunspot number. This study confirms that occurrence of Type III bursts correlate well with Sunspot number. Further, using the data obtained using e-CALLISTO network, we have investigated drift rates of isolated Type III bursts and duration of the group of Type III bursts. Since Type II, Type III and Type IV bursts are signatures of solar flares and/or CMEs, we can use the radio observations to predict space weather hazards. In this article, we have discussed two events that have caused near Earth radio blackouts. Since e-CALLISTO comprises more than 152 stations at different longitudes, we can use it to monitor the radio emissions from the solar corona 24 h a day. Such observations play a crucial role in monitoring and predicting space weather hazards within few minutes to hours of time.     

Electrooptical navigation for aircraft

Concurrently with the development of guidance laws for low-altitude rotorcraft flight operations, efforts are underway to develop automated systems for locating the terrain and the obstacles using inputs from passive electrooptical sensors such as TV cameras and infrared imagers. A passive obstacle location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given     

Improving performance in pulse radar detection using neuralnetworks

A new approach using a multilayered feed forward neural network for pulse compression is presented. The 13 element Barker code was used as the signal code. In training this network, the extended Kalman filtering (EKF)-based learning algorithm which has faster convergence speed than the conventional backpropagation (BP) algorithm was used. This approach has yielded output peak signal to sidelobe ratios which are much superior to those obtained with the BP algorithm. Further, for use of this neural network for real time processing, parallel implementation of the EKF-based learning algorithm is indispensable. Therefore, parallel implementation has also been developed