The Juno Magnetic Field Investigation

The Juno Magnetic Field investigation (MAG) characterizes Jupiter’s planetary magnetic field and magnetosphere, providing the first globally distributed and proximate measurements of the magnetic field of Jupiter. The magnetic field instrumentation consists of two independent magnetometer sensor suites, each consisting of a tri-axial Fluxgate Magnetometer (FGM) sensor and a pair of co-located imaging sensors mounted on an ultra-stable optical bench. The imaging system sensors are part of a subsystem that provides accurate attitude information (to ～20 arcsec on a spinning spacecraft) near the point of measurement of the magnetic field. The two sensor suites are accommodated at 10 and 12 m from the body of the spacecraft on a 4 m long magnetometer boom affixed to the outer end of one of ’s three solar array assemblies. The magnetometer sensors are controlled by independent and functionally identical electronics boards within the magnetometer electronics package mounted inside Juno’s massive radiation shielded vault. The imaging sensors are controlled by a fully hardware redundant electronics package also mounted within the radiation vault. Each magnetometer sensor measures the vector magnetic field with 100 ppm absolute vector accuracy over a wide dynamic range (to 16 Gauss = \(1.6 \times 10^{6}\mbox{ nT}\) per axis) with a resolution of ～0.05 nT in the most sensitive dynamic range (±1600 nT per axis). Both magnetometers sample the magnetic field simultaneously at an intrinsic sample rate of 64 vector samples per second. The magnetic field instrumentation may be reconfigured in flight to meet unanticipated needs and is fully hardware redundant. The attitude determination system compares images with an on-board star catalog to provide attitude solutions (quaternions) at a rate of up to 4 solutions per second, and may be configured to acquire images of selected targets for science and engineering analysis. The system tracks and catalogs objects that pass through the imager field of view and also provides a continuous record of radiation exposure. A spacecraft magnetic control program was implemented to provide a magnetically clean environment for the magnetic sensors, and residual spacecraft fields and/or sensor offsets are monitored in flight taking advantage of Juno’s spin (nominally 2 rpm) to separate environmental fields from those that rotate with the spacecraft.     

The canberra high altitude mission platform

This presents the capabilities of two English Electric Aviation Canberra aircraft owned by High Altitude Mapping Missions, Inc. These aircraft are available for high altitude commercial, government, and scientific missions. The basic specifications of the Canberra are provided and compared to other high-performance jet aircraft falling into the same category. This describes the high altitude flight characteristics and mission capabilities of the Canberras. The aircraft are configured to conduct up to eight-hour flight operations with up to six hours at 50,000 feet altitude. Shorter missions can be conducted at higher altitudes. Potential missions include: IFSAR, magnetic field mapping, gravity field mapping, imaging (SAR, IR, & hyper-spectral), LIDAR, communications relay, dropsonde deployment, hybrid rocket launching, severe storm monitoring, and disaster monitoring. Canberra high altitude operations have minimal weather impact on missions, are free from flight constraints imposed by air traffic control, can do large area coverage, and long mission times.     

多无人机协同覆盖路径规划

多无人机协同覆盖路径规划(CPP)由于其并行性和容错能力,对于提高无人机完成侦察、监视、搜索等任务的效率具有重要意义。提出了一种基于无人机任务性能评价和任务区域划分的多无人机协同CPP算法。定量分析了无人机执行覆盖任务的能力,根据无人机及携带成像传感器的性能给出了计算无人机任务性能指数的数学公式;提出了一种基于任务性能和子区域宽度的任务区域划分算法,使无人机的总转弯次数达到最少。仿真结果表明,所提出的CPP算法能够规划出全局最优的多无人机协同覆盖路径。     

Aging avionics and net-centric operations

The transformation to net-centric operations necessitates evaluation of existing avionics capabilities, identification of deficiencies of these avionics for net-centric operations, and evaluation of alternative avionics that can provide the needed capabilities. The Global Information Grid (GIG) enables net-centric operations. The purpose of the GIG is to provide end users real-time or near-real-time access to multiple information sources ranging from airborne/satellite/ground sensors (video imagery and processed visual information/data) to databases. The end users in an aircraft view and interact with this information through the human system interface (HSI) or "smart" displays. The information is transmitted across a Gigabit Ethernet on-board the aircraft that interfaces with multiple channels of a software programmable radio that acts as a hub in the GIG network, or on-board sensors and processors. This paper presents the mandated capabilities, and the processes involved in determination of upgrades needed to achieve net-centric operations.     

Space Interferometry Mission spacecraft pointing error budgets

Preliminary error budgets for the pointing knowledge, control, and stability of the Space Interferometry Mission (SIM) spacecraft are constructed using the specifications of commercial off-the-shelf attitude determination sensors, attitude control actuators, and other spacecraft capabilities that have been demonstrated in past missions. Results obtained indicate that we can meet all the presently known spacecraft pointing requirements. A large number of derived requirements are generated from this study. Examples are specifications on attitude determination sensors, attitude control actuators, minimum settling time after a rest-to-rest spacecraft slew. Preliminary error budgets constructed in this study must be updated to reflect the changing spacecraft design and requirements     

星际着陆自主障碍检测与规避技术

 为了在具有科学价值的复杂地形区域实现安全着陆,未来的星际着陆器必须具备自主障碍检测与规避的能力。从星际着陆导航传感器技术、自主障碍检测方法和自主障碍规避技术3个方面出发,对星际着陆自主障碍检测与规避技术进行较全面的分析和总结。首先,对适用于星际着陆自主障碍检测的各种主动式和被动式传感器的工作原理、优缺点进行较深入的阐述;接着,基于不同传感器的测量信息,对各种自主障碍检测方法的障碍检测能力、优缺点进行较详细的对比分析;然后,基于多信息融合的自主障碍检测方法,对安全着陆点选择的原则进行阐述;最后,对星际着陆自主障碍规避流程和适用于星际着陆自主障碍规避的制导控制方法进行较系统的总结。     

KUPS: Knowledge-Based Ubiquitous and Persistent Sensor Networks for Threat Assessment

We propose a knowledge-based ubiquitous and persistent sensor network (KUPS) for threat assessment, in which "sensor" is a broad characterization. It refers to diverse data or information from ubiquitous and persistent sensor sources such as organic sensors and human intelligence sensors. Our KUPS for threat assessment consists of two major steps: situation awareness using fuzzy logic systems (FLSs) and threat parameter estimation using radar sensor networks (RSNs). Our FLSs combine the linguistic knowledge from different intelligent sensors, and our proposed maximum-likelihood (ML) estimation algorithm performs target radar cross section (RCS) parameter estimation. We also show that our ML estimator is unbiased and the variance of parameter estimation matches the Cramer-Rao lower bound (CRLB) if the radar pulses follow the Swerling II model. Simulations further validate our theoretical results.     

Performance evaluation of multi-sensor classification systems

A common problem in classification is to use one/more sensors to observe repeated measurements of a target's features/attributes, and in turn update the targets' posterior classification probabilities to aid in target identification. This paper addresses the following questions: 1. How do we quantify the classification performance of a sensor? 2. What happens to the posterior probabilities as the number of measurements increase? 3. Will the targets be classified correctly? While the Kalman filter allows for off-line estimation of kinematic performance (covariance matrix), a comparable approach for studying classification accuracy has not been done previously. We develop a new analytical approach for computing the long-run classification performance of a sensor and also present recursive formulas for efficient calculation of the same. We show that, under a minimal condition, a sensor will eventually classify all targets perfectly. We also develop a methodology for evaluating the classification performance of multi-sensor fusion systems involving sensors of varying quality. The contributions of this paper are 1. A simple metric to quantify a sensor's ability to discriminate between the targets being identified, and its use in comparing multiple sensors, 2. An approximate formula based on this metric to compute off-line estimates of the rate of convergence toward perfect classification, and the number of measurements required to achieve a desired level of classification accuracy, and 3. The use of this metric to evaluate classification performance of multi-sensor fusion systems.     

无人机系统安全目标水平预估方法

考虑无人机系统（UAS）与有人机运行安全特性的不同,通过事件树分析识别出对地撞击是无人机系统运行的首要风险方式。基于等效安全水平的概念,建立确定无人机系统安全目标水平的对地撞击模型,将无人机撞击动能、构型参数以及飞行环境因素综合考虑到模型中,并计算了不同无人机系统在不同运行场景下的安全目标水平以及基于我国地域人口的安全目标水平,结果表明: 在考虑运行环境的情况下,对无人机系统安全目标水平的定量要求可能跨越4～5个数量级。在此基础上,结合风险矩阵的概念,给出基于对地撞击情况的无人机系统运行风险评价矩阵,为无人机系统运行风险评价提供了一种可行思路。      

角振动校准装置研究

为提升对惯性器件的动态性能评价能力,通过对被校传感器施加标准正弦角振动激励,精确测量角振动过程,实现了对角振动传感器的校准。基于不同频段的特点,将校准频段划分为低频和高频2部分,并提出空气轴承与无刷直流力矩电机相结合的低频角振动台方案,以及轻质空心杯精密空气轴承与框式电磁驱动结构相结合的高频角振动台方案;分别采用精密角度编码器和衍射光栅激光干涉仪实现对低频和高频角振动的测量,成功研制出频率范围为0.25~550Hz、角加速度范围为0.1~1 760rad/s2以及角速度波形失真小于2%的角振动绝对法校准装置。与德国国家物理技术研究院的角振动校准装置相比,该装置能够显著提升承载能力,可广泛用于惯性器件动态性能的测试与评价。     

A Smart Low-Power Meteorological System

A new low-power instrument to measure meteorological parameters has been developed. The instrument is based on an intelligent data cruncher concept: Fast sensor data rates are stored and process to yield a variety of answers for each parameter, at slower data rates, as appropriate. Special methods are used to achieve these results with an average current drain of under one mA, including sensors. Sampling rates and processing algorithms are designed to correct for swaying ocean-deployed buoys. A modular approach to design allows many types of sensors to be accommodated and permits data dissemination to a variety of destinations; data is available for real-time transmission or for internal archiving. The Weather Station's high-capacity internal data storage system, coupled with its fast data acquisition rates, enable the instrument to be used for air turbulence measurements.     

Atmospheric Science with InSight

In November 2018, for the first time a dedicated geophysical station, the InSight lander, will be deployed on the surface of Mars. Along with the two main geophysical packages, the Seismic Experiment for Interior Structure (SEIS) and the Heat-Flow and Physical Properties Package (HP³), the InSight lander holds a highly sensitive pressure sensor (PS) and the Temperature and Winds for InSight (TWINS) instrument, both of which (along with the InSight FluxGate (IFG) Magnetometer) form the Auxiliary Sensor Payload Suite (APSS). Associated with the RADiometer (RAD) instrument which will measure the surface brightness temperature, and the Instrument Deployment Camera (IDC) which will be used to quantify atmospheric opacity, this will make InSight capable to act as a meteorological station at the surface of Mars. While probing the internal structure of Mars is the primary scientific goal of the mission, atmospheric science remains a key science objective for InSight. InSight has the potential to provide a more continuous and higher-frequency record of pressure, air temperature and winds at the surface of Mars than previous in situ missions. In the paper, key results from multiscale meteorological modeling, from Global Climate Models to Large-Eddy Simulations, are described as a reference for future studies based on the InSight measurements during operations. We summarize the capabilities of InSight for atmospheric observations, from profiling during Entry, Descent and Landing to surface measurements (pressure, temperature, winds, angular momentum), and the plans for how InSight’s sensors will be used during operations, as well as possible synergies with orbital observations. In a dedicated section, we describe the seismic impact of atmospheric phenomena (from the point of view of both “noise” to be decorrelated from the seismic signal and “signal” to provide information on atmospheric processes). We discuss in this framework Planetary Boundary Layer turbulence, with a focus on convective vortices and dust devils, gravity waves (with idealized modeling), and large-scale circulations. Our paper also presents possible new, exploratory, studies with the InSight instrumentation: surface layer scaling and exploration of the Monin-Obukhov model, aeolian surface changes and saltation / lifing studies, and monitoring of secular pressure changes. The InSight mission will be instrumental in broadening the knowledge of the Martian atmosphere, with a unique set of measurements from the surface of Mars.     

REMS: The Environmental Sensor Suite for the Mars Science Laboratory Rover

The Rover Environmental Monitoring Station (REMS) will investigate environmental factors directly tied to current habitability at the Martian surface during the Mars Science Laboratory (MSL) mission. Three major habitability factors are addressed by REMS: the thermal environment, ultraviolet irradiation, and water cycling. The thermal environment is determined by a mixture of processes, chief amongst these being the meteorological. Accordingly, the REMS sensors have been designed to record air and ground temperatures, pressure, relative humidity, wind speed in the horizontal and vertical directions, as well as ultraviolet radiation in different bands. These sensors are distributed over the rover in four places: two booms located on the MSL Remote Sensing Mast, the ultraviolet sensor on the rover deck, and the pressure sensor inside the rover body. Typical daily REMS observations will collect 180 minutes of data from all sensors simultaneously (arranged in 5 minute hourly samples plus 60 additional minutes taken at times to be decided during the course of the mission). REMS will add significantly to the environmental record collected by prior missions through the range of simultaneous observations including water vapor; the ability to take measurements routinely through the night; the intended minimum of one Martian year of observations; and the first measurement of surface UV irradiation. In this paper, we describe the scientific potential of REMS measurements and describe in detail the sensors that constitute REMS and the calibration procedures.     

Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

Unmanned Aircraft Systems (UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management (ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider (ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to: (A) describe what typical ANSP-supplied UAS Traffic Management (UTM) architecture is required to facilitate all types of civil UAS operations; (B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace; (C) outline future directions and challenges related with UAS operations for the ANSP.     

Ultimate IR Horizon Sensor

The accuracy of presently available IR horizon sensors is not sufficient to meet the stringent attitude sensing and control requirements for future remote sensing and meteorological satellites. The different sources of error in a horizon sensor are analyzed. The accuracy of the sensor is presently limited by the detector noise. Use of HgCdTe in place of an immersed bolometer detector, which is used in conventional horizon sensors eliminates many of the errors. Hence, it is possible to design an ultimate IR horizon sensor whose accuracy is limited only by the uncertainty of the Earth horizon. Comparison of performances of the two types of detectors for horizon sensing is given and possible configurations of sensor using this detector are discussed.     

Multisensor multitarget bias estimation for general asynchronous sensors

A novel solution is provided for the bias estimation problem in multiple asynchronous sensors using common targets of opportunity. The decoupling between the target state estimation and the sensor bias estimation is achieved without ignoring or approximating the crosscovariance between the state estimate and the bias estimate. The target data reported by the sensors are usually not time-coincident or synchronous due to the different data rates. Since the bias estimation requires time-coincident target data from different sensors, a novel scheme is used to transform the measurements from the different times of the sensors into pseudomeasurements of the sensor biases with additive noises that are zero-mean, white, and with easily calculated covariances. These results allow bias estimation as well as the evaluation of the Cramer-Rao lower bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases in any scenario. Monte Carlo simulation results show that the new method is statistically efficient, i.e., it meets the CRLB. The use of this technique for scale and sensor location biases in addition to the usual additive biases is also presented.     

Raman Spectroscopy—A Powerful Tool for in situ Planetary Science

This paper introduces Raman spectroscopy and discusses various scenarios where it might be applied to in situ planetary missions. We demonstrate the extensive capabilities of Raman spectroscopy for planetary investigations and argue that this technique is essential for future planetary missions.     

RPC-MAG The Fluxgate Magnetometer in the ROSETTA Plasma Consortium

The fluxgate magnetometer experiment onboard the ROSETTA spacecraft aims to measure the magnetic field in the interaction region of the solar wind plasma with comet 67P/Churyumov-Gerasimenko. It consists of a system of two ultra light (about 28 g each ) triaxial fluxgate magnetometer sensors, mounted on the 1.5 m long spacecraft boom. The measurement range of each sensor is ±16384 nT with quantization steps of 31 pT. The magnetometer sensors are operated with a time resolution of up to 0.05 s, corresponding to a bandwidth of 0–10 Hz. This performance of the RPC-MAG sensors allows detailed analyses of magnetic field variations in the cometary environment. RPC-MAG furthermore is designed to study possible remnant magnetic fields of the nucleus, measurements which will be done in close cooperation with the ROSETTA lander magnetometer experiment ROMAP.     

Bayesian Approach to Extended Object and Cluster Tracking using Random Matrices

In algorithms for tracking and sensor data fusion the targets to be observed are usually considered as point source objects; i.e., compared with the sensor resolution their extension is neglected. Due to the increasing resolution capabilities of modern sensors, however, this assumption is often no longer valid as different scattering centers of an object can cause distinct detections when passing the signal processing chain. Examples of extended targets are found in short-range applications (littoral surveillance, autonomous weapons, or robotics). A collectively moving target group can also be considered as an extended target. This point of view is the more appropriate, the smaller the mutual distances between the individual targets are. Due to the resulting data association and resolution conflicts any attempt of tracking the individual objects within the group seems to be no longer reasonable. With simulated sensor data produced by a partly unresolvable aircraft formation the addressed phenomena are illustrated and an approximate Bayesian solution to the resulting tracking problem is proposed. Ellipsoidal object extensions are modeled by random matrices, which are treated as additional state variables to be estimated or tracked. We expect that the resulting tracking algorithms are also relevant for tracking large, collectively moving target swarms.     

垂直起降无人机总体方案分析及控制策略综合研究

垂直起降无人机是垂直起降技术和无人机的结合体。它既有直升机的垂直起降和悬停能力,又具有固定翼飞机的速度快、航程远的特点。同时,它还具备一般无人机的基本特点,可满足执行特殊任务的需要。因无需考虑机载人员的因素,垂直起降无人机可以采用的垂直起降和总体设计方案更加灵活和多样。本文在分析现有各种垂直起降无人机方案的基础上,提出了“双旋翼尾坐式飞翼”布局,并在随后对其进行了详细参数确定和性能估算。最后,对其进行了控制策略的研究。