MPC

The Auto-Router, Sensor Footprint, RF Line-Of-Sight, and Route & Area Nomination Algorithms can be combined to create a powerful mission analysis, image planning, and collision avoidance application.

MISSION PLANNING COMPONENTS - MPC

The result is the capability to effectively and efficiently plan a mission, avoid terrain, avoid obstacles, and gather information on whether or not the desired EO/IR imagery can be obtained – all in near-real-time.

Auto-Routing

This component finds the most efficient path around obstacles in real-time. Kutta’s auto-router has been proven in Monte-Carlo simulations to achieve routing around a randomized mix of 50 to 100 circles and polygons in under an average time of 0.12 msec on an Intel 1 GHz processor. All flight planning modes work in conjunction with the integrated auto-routing algorithm. Inputs: Circular or polygon (convex or concave) no-fly zones, starting waypoint, goal waypoint. Output: Multi-waypoint path to achieve goal waypoint.

The Radio-Frequency Line-of-Sight component allows an operator to easily define the Radio-Frequency (RF) characteristics of the transmit and receive power of the Unmanned Aircraft System (UAS). Using a Digital Terrain Elevation Model (DTED), Kutta’s efficient RF LOS algorithm determines the vertices of a polygon, where 100% RF coverage from the Ground Control Station (GCS) to the unmanned vehicle exist. The vertices of the resulting area are provided in modular fashion for display on mapping applications. Inputs: Location of antenna, RF characteristics, environmental and terrain conditions, vehicle performance characteristics, DTED data. Outputs: Vertices of a polygon, STANAG 4586 private messages.

Sensor Footprint

This extremely efficient Sensor Footprint component gathers real-time input from the unmanned vehicle’s position (latitude, longitude, altitude) and the pan, tilt, zoom parameters of an EO/IR payload to determine the sensor’s actual projection onto the ground. Since the algorithm takes into account Digital Terrain Elevation Data (DTED), the sensor footprint can be overlaid in both 2D and 3D environments, offering exceptional situational awareness of where the sensor has pointed, where it is pointing, and where it is capable of pointing. Inputs: Vehicle position and orientation, payload pan, tilt, zoom parameters, DTED, NIIRS rating. Outputs: Vertices of a polygon and polygon fill parameters.

The Route Nomination component provides the capability to select a route or designate an area to survey. The algorithm determines an optimum flight plan that keeps the Air Vehicle (AV) within defined airspace restrictions, allows the AV to avoid terrain, and gather the designated imagery based on pertinent mission planning characteristics (i.e. dwell time, image overlap, object detection size, etc). It then outputs a STANAG 4586 compliant flight plan and a series of payload commands that can be sent to the AV for execution. Inputs: Select route or Points of Interest (POI) to survey. Outputs: Air Vehicle (AV) stare points, and loiter points.

Airspace Management

This component allows a user to input Restricted Operating Zones (ROZs), fly zones, and flight corridors defined by airspace management authorities. Kutta’s algorithm merges the zones and flight corridors with the RF LOS coverage to define a Safe Airspace Volume (SAV). The result provides a visual reference to ensure the unmanned vehicle’s flight path remains within the defined SAV. Inputs: Safe Airspace Zones (SAV), Restricted Operating Zones (ROZ), and Radio Frequency Light-of-Sight (RF-LOS) data. Outputs: Safe Airspace Volume with bounding points.

Kutta licenses sophisticated operating system independent STANAG 4586 Vehicle Specific Modules (VSMs) for some of the most advanced Unmanned Aircraft System (UAS) Auto-Pilots on the market. The VSM has been tested in Hardware In-the-Loop Simulators as well as in flight tests with a STANAG-compliant Common UAV Control Stations (CUCS). Kutta currently licenses the Data Link Interface (DLI) and the VSMs for Cloud Cap Piccolo’s, Procures’s Kestrel, and MLB’s BAT 3. imagery based on pertinent mission planning characteristics (i.e. dwell time, image overlap, object detection size, etc). It then outputs a STANAG 4586 compliant flight plan and a series of payload commands that can be sent to the AV for execution. Inputs: Select route or Points of Interest (POI) to survey. Outputs: Air Vehicle (AV) stare points, and loiter points.

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