MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the CONVAIR 580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.
In early 2015, the NASA Glenn Research Center will conduct a field campaign based out of Cleveland, Ohio with 60 flight hours on the Twin Otter icing research aircraft. The purpose of the field campaign is to test several prototype algorithms meant to detect the location and severity of in-flight icing within the terminal airspace. The terminal airspace is currently defined as within 25 kilometers horizontal distance of the terminal, which in this case was Hopkins International Airport in Cleveland. Two new and improved algorithms have been developed and will be operated during the field campaign. The first is the 'NASA Icing Remote Sensing System', or NIRSS. NASA and the National Center for Atmospheric Research have developed this icing remote sensing technology which has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station1,2.
Abstract To reduce the number and severity of accidents, automakers have invested in active safety systems to detect and track neighboring vehicles to prevent accidents. These systems often employ RADAR and LIDAR, which are not degraded by low lighting conditions. In this research effort, reflections from deer were measured using two sensors often employed in automotive active safety systems. Based on a total estimate of one million deer-vehicle collisions per year in the United States, the estimated cost is calculated to be $8,388,000,000 . The majority of crashes occurs at dawn and dusk in the Fall and Spring . The data includes tens of thousands of RADAR and LIDAR measurements of white-tail deer. The RADAR operates from 76.2 to 76.8 GHz. The LIDAR is a time-of-flight device operating at 905 nm. The measurements capture the deer in many aspects: standing alone, feeding, walking, running, does with fawns, deer grooming each other and gathered in large groups.
Abstract Nowadays active collision avoidance has become a major focus of research, and a variety of detection and tracking methods of obstacles in front of host vehicle have been applied to it. In this paper, laser radars are chosen as sensors to obtain relevant information, after which an algorithm used to detect and track vehicles in front is provided. The algorithm determines radar's ROI (Region of Interest), then uses a laser radar to scan the 2D space so as to obtain the information of the position and the distance of the targets which could be determined as obstacles. The information obtained will be filtered and then be transformed into cartesian coordinates, after that the coordinate point will be clustered so that the profile of the targets can be determined. A threshold will be set to judge whether the targets are obstacles or not. Last Kalman filter will be used for target tracking. To verify the presented algorithm, related experiments have been designed and carried out.
Small and Lightweight Innovative Obstacle Detection Radar System for the General Aviation: Performances and Integration Aspects
Since 2011, ROD Ltd. and Boggi srl have started to cooperate in the field of airborne platform safety through the development and the integration of an innovative radar system, based on the radar system patented by in 2009 . ROD Ltd. is a startup company, created in 2011, in order to commercialize an innovative Obstacle and Terrain Avoidance Sensor concept (OTAS™). Boggi srl is an EASA DOA (21.J.453)  that has developed the capability of designing and certifying aerospace components from small changes to complex systems such as Remotely Piloted Air System (RPAS) or mission avionic. The direct experience of the operators in general aviation has shown that a number of accidents occur because of collisions with obstacles and, especially, but not only, with cables. During the years of 1997-2009, a total of 996 reported aviation accidents/collisions involving wires/power lines occurred in the United States. Of the 996 accidents, 301 involved at least one fatality .
This paper describes the development of a compact and low cost millimeter wave doppler radar sensor (77 GHz band), which can measure the vehicle ground speed precisely. The sensor has three unique features: First, all the radio frequency components are integrated into a single chip, including a millimeter wave transceiver and an on-chip antenna. Then, the chip package is made of plastic resin without use of expensive ceramic. Finally, a tiny dome-shaped resin lens is attached to the chip to collimate waves. These technologies enable the sensor to measure 53 x 71 x 65 mm₃, to weigh 115 grams. Compared to a conventional optical measuring instrument, for example, the sensor weighs only about fifteenth and is one-fifth of the size, while the measurement accuracy is almost comparable. So this sensor seems to have a variety of potential applications. In this paper, we also considered the feasibility of some other applications than just measuring ground speed.
In-flight Icing Hazard Verification with NASA's Icing Remote Sensing System for Development of a NEXRAD Icing Hazard Level Algorithm
From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.
In recent years the number of vehicles equipped with millimeter wave radar has been increasing due to the popularization of driving assistance systems such as adaptive cruise control (ACC) and forward vehicle collision warning (FCW) systems. Consequently, high performance millimeter wave radar must be developed to support even more advanced driving assistance systems. The investigation described in this paper confirms that it is possible to use high range resolution radar to recognize the width of a target. In tests, a simulated radar signal was transmitted and received by a millimeter waveband network analyzer using a 1.6 meter-wide aluminum foil board as the target. When the range resolution was low, only one point of reflection from the board could be detected. However, when the range resolution was improved, then multiple points of reflection from the target could be detected.
In-door simulation of Pass By Noise [PBN] Testing of a car was successfully attempted on a chassis dynamometer in a full-scale Vehicle Semi-Anechoic Chamber [VSAC]. The work has a practical approach for quick testing of vehicles to be submitted for certification. It has 3 parts: 1 Confirmation of overall Indoor PBN Testing as per ISO 362-1:2007 (E)2 Correlation of the PBN-results obtained on the Track with those in the VSAC as per both Method A and [proposed] Method B based on vehicle-acceleration depending on Power to Mass Ratio of the Test-vehicle3 Use of this In-door simulation for quick evaluation of design modifications of the vehicle to meet its PBN Limit with a safe margin Optimum no. of microphones was sought out in VSAC to reduce the set-up time without sacrificing accuracy of the results. Dyno-roller / tyre radiated noise need be reduced to have the close correlation with the Track results.
In the era of low cost product, enormous pressure to keep product development cost and time as low as possible. Durability verification and validation always consume big amount of product development cost and time. This paper gives low cost and quick, durability virtual verification which can be tested by running vehicle on track to check correlation. In this low cost durability verification, maximum stress levels on Frame and Cabin are generated analytically at all hot spot location based on finite element inertia relief analysis. Basic input load data is acquired by running proto type vehicle on track. Mathematical loading spectrum (Range Vs Cycle-Cumulative frequency distribution) for track is evaluated from acquired data. Stress spectrums are generated analytically for all hot spot locations based on mathematical load spectrum. Analytically component S-N curve for frame, cabin components with different slops [1,2] is generated based on material ultimate tensile stress values.
Edgewater's RTEdge™ Platform toolset is a model driven development environment for mission critical real-time systems. Using precise execution semantics and mathematical proof-based analysis, RTEdge™ enables the verification of critical properties of systems with high assurance. This case study will follow the design and implementation life-cycle of a system representing a real-world, mission critical domain: airborne electronic warfare. Using examples and constraints taken from this system, software components will be built to illustrate the principles of architectural conformance, timeliness and testing as executed within a static analysis framework. Using RTEdge™ as an example, this case study will introduce the concepts of model driven development in software and demonstrate how static analysis can be used to verify characteristics of a system that are traditionally left for later stages of development.
The Eaton VORAD Collision Warning System is utilized by many commercial trucking companies to improve and monitor vehicle and driver safety. The system is equipped with forward and side radar sensors that detect the presence and movements of vehicles around the truck to alert the driver of other vehicles' proximity. When the sensors detect that the host vehicle is closing on a vehicle ahead at a rate beyond a determined threshold, or that a nearby vehicle is located in a position that may be hazardous, the system warns the driver visually and audibly. The system also monitors parameters of the vehicle on which it is installed, such as the vehicle speed and turn rate, as well as the status of vehicle systems and controls. The monitored data is also recorded by the VORAD system and can be extracted in the event that the vehicle is involved in an accident.
The Sentinel-1 Mission is part of the Global Monitoring for Environment and Security (GMES) initiative whose overall objective is to support Europe's goals regarding sustainable development and global governance of the environment by providing timely and quality data, information, services and knowledge. The Sentinel-1 satellite is commissioned by ESA with Thales Alenia Space Italy as prime contractor and Astrium Germany as subcontractor for the Sentinel-1 SAR instrument. Sentinel-1 is an imaging radar mission at C-band aimed at providing continuity of data for user services. In particular, Sentinel-1 is aimed at providing data to the sea ice zones and the arctic environment, to surveillance of marine environment (wind speed, oil spill and ship detection) to monitoring and mapping land surfaces, and mapping in support of humanitarian aid in crisis situations.
Communication in Future Vehicle Cooperative Safety Systems: 5.9 GHz DSRC Non-Line-of-Sight Field Testing
Dedicated Short Range Communication (DSRC) is increasingly being recognized as the protocol of choice for vehicle safety applications by Original Equipment Manufacturers (OEMs) and road operators. DSRC offers the ability to communicate effectively from vehicle-to-vehicle and from vehicle to infrastructure with low latency and high reliability. A wide range of applications have been conceptualized to support safety, mobility and convenience, including: cooperative collision avoidance, travel information, and electronic payment. To be effective, infrastructure-based applications require an installed-vehicle base along with infrastructure deployment, while vehicle-to-vehicle applications require significant DSRC market penetration along with some degree of infrastructure support systems. Some vehicles currently include safety applications involving forward looking radar. The radar supplies information about objects, their distances and relative speed ahead of the host vehicle.
Model of an Effective System for Dangerous Objects as a Contribution to Active Safety in Automotive Applications
Developments in electronics and mechanics have improved performance of vehicles in collision, especially during and after the crash, producing injuries and an economical impact to the owner of the vehicle. Lately several projects focused on preventing collision have raised as Active Safety Systems or so called in Europe, Advanced Driving Assistance Systems which have been developed facing the challenge of avoiding collisions. The goal of this project is to design, build and install a system capable of detecting and warning the driver about dangerous obstacles. In case the driver does not react on time the system will slow down the vehicle in order to decrease the collision velocity, or even avoid it. After a careful analysis of different LIDAR and non-vision passive infrared sensors are implemented and explored. This paper proposes a decision model using the combinations of some simple models of the driver, the vehicle, the control unit, and obstacle detection.
Automotive radar application is a focus in active traffic safety research activities. And accurate lateral position estimation from the leading target vehicle through radar is of great interest. This paper presents a method based on the regression tree, which estimates the rear centroid of leading target vehicle with a long range FLR (Forward Looking Radar) of limited resolution with multiple radar detections distributed on the target vehicle. Hours of radar log data together with reference value of leading vehicle's lateral offset are utilized both as training data and test data as well. A ten-fold cross validation is applied to evaluate the performance of the generated regression trees together with fused decision forest for each percentage of the training data.
Increasing market penetration of driver assistance systems challenges system suppliers with ACC (Adaptive Cruise Control) and PSS (Predictive Safety Systems) functions with divergent requirements. This paper covers the technical development of a long range radar sensor that can address the requirements for high-performance systems as well as requirements for cost-efficient sensor components with robust and compact design and high quality standards, which are suited for high-volume production.
An obstacle recognition algorithm for the Pre-Crash Safety system has been newly developed with a stereo vision system and a millimeter wave radar with additional functions. This algorithm uses the merits of both the millimeter wave radar and the stereo vision system, and has two main features. One feature utilizes the merits of the stereo vision system detection with the detection results from the millimeter wave radar allowing for a more detailed horizontal position and width of the obstacle. This enables the equipment to operate at an earlier stage according to how well the relationship between the vehicle and the obstacle is understood. Another feature fuses detection from the millimeter wave radar and the stereo vision system. This system has succeeded in enhancing the detection performance of pedestrians who have been more difficult to detect than reflective objects such as cars.
In fatal accidents due to heavy duty trucks, the fatalities of occupants in passenger cars in which rear-end collision occur account for the largest percent. Collisions to the vehicles in traffic jams and collision to other accidents scenes on express ways can result in serious repercussions. Therefore the system which reduces the damage of collisions has long been demanded and here the world-first Pre-crash Safety (PCS) System for heavy duty trucks was developed. This system gives warning to the driver in case there is a possibility of collision with preceding vehicles, and activates the brakes to mitigate damage in case there is a higher possibility of collision. In order to get the maximum effect on the express ways where the trucks are in high speed, it is necessary to give warning and activate the brakes with relatively early timing.
Driver support systems without active vehicle interaction are convenience functions and can be viewed as a pre-stage to vehicle guidance and collision avoidance. By information to or an early warning of the driver a quicker reaction of the driver can be achieved. Today, Long Range Radar (LRR) and Lidar are used for the ACC function. With a range of up to 200m and superior signal quality, LRR is the key technology and main enabler for future predictive safety systems. Video technology has been introduced in a German Luxury class vehicle in 2005 for a system for night vision improvement. Also passive infrared sensing based thermal radiation sensors are used in other systems. Mid and short range applications are covered by various technologies based on Radar and optical sensing as well as on emerging new technologies. The highest demand regarding performance and reliability is put on active safety systems.
We propose a novel millimeter wave radar system and object detection algorithm for automobile use by using advanced null scanning method. Generally, null scanning method can achieve a higher resolution and a more compact sensor size compared to beam scanning method, but needs huge computing power. We introduced the theory of forgetting factor into it and developed a new null scan algorithm. It achieved a high lateral object separation ability of less than 3 degree, and a quick response under feasible computing power in simulation and test vehicle. These technologies enable compact and high performance radar for advanced safety system.
The future of vehicle safety will benefit greatly from precrash detection - the ability of a motor vehicle to predict the occurrence of an accident before it occurs. There are many different sensor technologies currently available for pre-crash detection. However no single sensor technology has demonstrated enough information gathering capability within the cost constraints of vehicle manufacturers to be used as a stand alone device. A proposed solution consists of combining information from multiple sensors in an intelligent computer algorithm to determine accurate precrash information. In this paper, a list of sensors currently available on motor vehicles and those that show promise for future development is presented. These sensors are then evaluated based on cost, information gathering capability and other factors.
Enhancing the capabilities of established airframes to meet expanded mission requirements is preferential to the design of specialized aircraft. The high cost associated with the research and development of a specialized aircraft platform has shifted the concentration towards the modification of existing aircraft to support multiple C4ISR missions. The recently developed Oculus sensor deployment system is one such example of this trend, providing a fully integrated aerial visual enhancement platform with multi-mission capabilities. This paper provides a short survey of the Oculus sensor pallet system and overviews some of the multiple guidelines used which ensure that various remote sensing technologies may be securely and simultaneously deployed.
Radarsat-2 is a commercial Synthetic Aperture Radar satellite for earth observation.  The general stowed configuration is shown in Figure 1. In nominal operation mode, once deployed, the large SAR polarimetric Antenna (i.e. able to transmit and receive both horizontal and vertical polarisations) is inclined of about -29.8° versus the nominal direction of geodetic local surface normal (Right Looking mode). When is necessary to take images of South Pole, nominally not visible from SAR, the S/C must be rotated to the +29.8° position (Left Looking mode). During the Radarsat-2 thermal testing the S/C (PFM) was subjected to a first thermal balance/thermal cycling test in vacuum with simulation of external heat fluxes by means of I/R lamps and additional test heaters. A very complex thermal test configuration was required in order to simulate the continually varying thermal environment imposed by the S/C nominal sun-synchronous orbit and attitude.
There is increasing international interest in collision avoidance and more recently in safety systems for ‘Vulnerable Road Users’ (VRUs). The aim of the ‘Advanced Protection for Vulnerable Road Users’ (APVRU) project was to develop a sensor system capable of detecting VRUs, distinguishing them from the road environment, tracking their position and predicting potential impacts with the vehicle. Our fusion of sensor data from multiple, short range, high accuracy, pulse radar units and a low-resolution passive infrared sensor array serves to eliminate the majority of clutter by negating false triangulation combinations, whilst ensuring that only thermally distinct moving targets are considered. The intention is that a derivative of the sensor system may eventually provide the technological link between VRU detection and a driver warning, collision avoidance and/or the activation of a safety system on the vehicle (external airbags).
Principle of the target tracking method for the Adaptive Cruise Control (ACC) system, which is applicable to non-uniform or transient condition, had been proposed by one of the authors. This method does not need any other information rather than that from the radar and host vehicle. Here the method is modified to meet more complex traffic scenarios and then applied to data measured on real highway. The modified method is based on the phase chart between the lateral component of the relative velocity and azimuth of a preceding vehicle. From the trace on the chart, the behavior of a preceding vehicle is judged and the discrimination between the lane change and curve-entry/exit can be made. The method can deal with the lane-change of a preceding vehicle on the curve as well as on the straight lane. And it is applied to more than 20 data including several road/vehicle conditions: road is straight, or turns right or left; vehicles are motorbikes, sedans and trucks.
Aviation Data Integration System (ADIS) project explores methods and techniques for integrating heterogeneous aviation data to support aviation problem-solving activity. Aviation problem-solving activities include: engineering troubleshooting, incident and accident investigation, routine flight operations monitoring, flight plan deviation monitoring, safety assessment, maintenance procedure debugging, and training assessment. To provide optimal quality of service, ADIS utilizes distributed intelligent agents including data collection agents, coordinator agents and mediator agents. This paper describes the proposed agent-based architecture of the Aviation Data Integration System (ADIS).
Blind areas around construction equipment are a major contributing factor in incidents involving a piece of equipment striking a worker. In highway construction, these types of incidents result in an average of 22 deaths a year in the United States. The Spokane Research Laboratory of the National Institute for Occupational Safety and Health, in cooperation with the Washington State Department of Transportation, is evaluating methods to decrease these incidents. One such method uses devices that assist equipment operators in monitoring blind areas around the equipment to prevent collisions with workers or other objects. Several camera and sensor systems are available for this application. These systems were evaluated on various trucks used in road construction and maintenance. Tests were conducted on sanding trucks during the winter months, which allowed researchers to investigate the effectiveness and limitations of various technologies under the most extreme conditions.
The increase in automobile accidents has heightened the awareness of safety in the general public, and serious safety measures have been pushed forward in various countries. Although those efforts have achieved a certain level of success, more effective methods are needed to cope with further increases of automobile ownership.Besides the collision safety, measures that prevent accidents or reduce the possibility of accidents will now be necessary to reduce the number of injuries.Here, we will present the current development status and issues for an obstacle recognition system that reduces the likelihood of accidents by utilizing radars and image sensors.
Accurately aligning and assembling large structures has traditionally been accomplished via fixed assembly tools and a skilled mechanic's eye. Advancements in measurement technology have facilitated the automation of the alignment process but its use has been limited due to difficulty in measuring and monitoring the join features during the alignment process. A newly developed method that combines the capabilities of Arc Second's IRGPS system along with Leica's Scanning Laser Radar technology provides an alternative means to automate the assembly and alignment of large complex structures.