A typical airborne ground surveillance radar is a multimode system with a ground moving target indicator (GMTI) mode
for surveillance and tracking of moving ground targets and synthetic aperture radar (SAR) modes for imaging of terrain
features and stationary ground targets. One of the key features of the GMTI mode is the ability to perform wide area
surveillance (WAS) of a substantial ground area, and in addition to provide persistent surveillance of a pre-specified
ground area over a long period of time. The accomplishment of this task requires careful optimization of radar
parameters and careful planning of the platform orbits so as to minimize the time spent turning the aircraft and
repositioning the radar. This paper defines the notion of surveillance orbit efficiency which, for constant speed flight, is
simply the percentage of time spent on the straight legs of a race track orbit. It then examines the orbit efficiency for
each of three cases depending on the assumed radar azimuth field of view (FOV). This paper is a modified version of
work described in a MITRE Technical Report for the US Army.
The increasing use of airwaves for military communication and surveillance and commercial applications places burdens on spectrum use. This crowding of the spectrum presents two broad problem categories. The first is "co-site interference" where numerous transmitters and receivers are physically located in a small area and share a given portion of the spectrum. Under these conditions, a receiver can be "victim" to a co-located transmitter. The second category involves numerous transmitters (typically airborne) well separated from each other but communicating to receivers placed in a relatively small area. The Common Data Link (CDL) refers to a standard protocol for military data delivery and communication. Surveillance platforms such as Tactical Unmanned Aerial Vehicles (TUAV), JSTARS, U2's, Global Hawks will stream high rate surveillance data (radar, visual and/or infrared imagery, etc.) down to ground terminals. As such, bandwidths are wide (100's MHz) and the potential exists for ground receivers to be victim to signals from airborne transmitters other than its desired source. MITRE has developed a CDL Interference Model to assess potential problems in realistic tactical surveillance scenarios. This paper documents the physical basis of the CDL Interference Model as well as the visualization software architecture that integrates the model with ModSAF/OneSAF.
Traditional antipersonnel land mines are an effective military tool, but they are unable to distinguish friend from foe, or civilian from military personnel. The concept described here uses an advanced moving target indicator (MTI) radar to scan the minefield in order to detect movement towards or within the minefield, coupled with visual identification by a human operator and a communication link for command and control. Selected mines in the minefield can then be activated by means of the command link. In order to demonstrate this concept, a 3D, interactive simulation has been developed. This simulation builds on previous work by integrating a detailed analytical model of an MTI radar. This model has been tailored to the specific application of detection of slowly moving dismounted entities immersed in ground clutter. The model incorporates the effects of internal scatterer motion and antenna scanning modulation in order to provide a realistic representation of the detection problem in this environment. The angle information on the MTI target detection is then passed to a virtual 3D sight which cues a human operator to the target location. In addition, radar propagation effects and an experimental design in which the radar itself is used as a command link are explored.
The common ground station (CGS) receives data from the joint surveillance and target attack radar system aircraft and from other airborne platforms. High-resolution imagery such as that provided by an unmanned airborne vehicle (UAV) carrying an IR and/or synthetic aperture radar (SAR) sensor will be incorporated into an advanced imagery CGS operation. While this level of integration provides a wealth of valuable information, it also increase the complexity of planning, assessment and exploitation which in turn dictates flexible simulation tools for mission rehearsal and operator training. MITRE has developed a ModSAF-driven model for a UAV equipped with a moving target indicator (MTI) radar for wide-area surveillance, and a battlefield combat identification system for positive identification of friendly forces. The imaging functions are performed by integrating the UAV model with visualization software in order to render the sensor's view in real-time. This model forms the basis for a multisensor CGS simulation controls imaging task assignments which taken place when an MTI track is selected for imaging by means of a mouse click entry on an active MTI display. At that time, the UAV is commanded to fly an automatically determined trajectory in order to align MTI display. At that time, the UAV is commanded to fly an automatically determined trajectory in order to align itself for the imaging task. A beam footprint whose position, size and shape is determined by the sensor position, attitude, and field-of-view appears on the display as an indication of the relationship of the image display to the terrain in the operational scenario. A 3D visualization of the designated target area then takes place on a separate display.
This paper reports on the continuing development of a DIS- compliant model for an airborne platform carrying a multisensor payload. This payload consists of a moving target indicator (MTI) radar, a cooperative battlefield combat identification system (BCIS), and imaging sensors. The imaging sensors are a synthetic aperture radar (SAR) and a forward looking infrared (FLIR) imager. The entire platform model is an extension to the ModSAF environment. The sensor model code is fully portable and integrated as ModSAF libraries. Relevant emission protocol data units (PDU) are generated and transmitted. The overall simulation architecture and the MTI and BCIS models have been described in detail elsewhere. The current work concentrates on the development of real-time model-based imaging functions. The software tools which provide this capability are available both in the government- owned inventory and as commercial products. The purpose of the current activity is to investigate the feasibility of integrating software of this kind with the ModSAF environment in order to produce realistic target/scene rendering similar to those obtained by high-resolution imaging sensors. To this end, we investigated real-time scene generation using two approaches. The first, through integration of the IRMA software package developed and distributed by the USAF Wright Laboratories, Eglin AFB, and the second is by use of the commercial software package SensorVisionTM, which is marketed and distributed by Paradigm Solutions, Inc. Both of these produce scene renderings in user specified wavebands by combining entity state PDU information with terrain data. The scene model information is passed to rendering software to produce an IR or SAR rendering of the scene.
We present a novel approach for implementing and optimizing an Automatic Target Recognition (ATR) algorithm for Synthetic Aperture Radar (SAR) imagery using the Princeton Engine (PE), a general purpose massively parallel single instruction multiple data (SIMD) machine. This approach was developed in the Algorithm Understanding Laboratory (AUL), a unique facility which is chartered to assist algorithm developers through high-speed implementation and near real-time visualization, and is located within the National Information Display Laboratory (NIDL). The PE architecture automatically provides a high speed-up directly proportional to the width of the image being processed, thereby reducing the train/test cycle times of ATR algorithms from days and hours down to minutes. Given this speed-up, the user can now train the system to classify a set of objects and then test it rapidly, thus tightening the train/test loop. With our approach, one can operate on the entire image, retaining useful image information until the very last stage in the algorithm.
The signal processing for a down-looking airborne radar requires that the input signal data be compensated for platform motion and terrain variations. Typical examples are a Moving Target Indicator (MTI) function in a surveillance radar where the ground clutter must be maintained around zero Doppler in order to accurately detect moving targets, and a Synthetic Aperture Radar (SAR) where the correct location of the reflectivity of a scatterer depends on maintaining an accurate Doppler centroid for each pixel position. Platform motion compensation can be complicated by a wide elevation beam which intercepts many range cells at each azimuth, forcing the compensation of many range cells with the platform rates. These platform rates are assumed to be available from on-board inertial navigation system (INS), and the motion compensation correction can be obtained using the INS inputs. Processing of ground returns will be further complicated by the lack of reliable terrain information which can introduce significant Doppler errors into the motion compensation. Such errors will have an effect on the motion compensation, hence on the positioning of ground returns in the Doppler domain. Variations due to local topography are impossible to model accurately without prior knowledge of the terrain.