East Syracuse, NY, United States

Sensis Corporation

sensis.com
East Syracuse, NY, United States

The Saab Sensis Corporation is a company based in DeWitt, New York. Sensis specializes in radar and passive sensors for airport surveillance and air defense. Sensis is the prime contractor for the ASDE-X air traffic control system which is used by the FAA at 34 US airports. ASDE-X uses airport surveillance radar, automatic dependent surveillance-broadcast, multilateration and surface movement radar to pinpoint the locations of aircraft and vehicles on the airport surface and airspace.In 2006, Sensis Corporation, in partnership with many other local CEOs from growing companies in Syracuse, formed The Famous Entrepreneurs Series. Anaren Inc., Clear Channel Communications, Communigration, Dolphin Technologies, O’Brien & Gene, PPC, SRC and United Radio were some of the other FES founding companies. The Famous Entrepreneurs Series is a lecture series that hosts quarterly lectures, seeking to encourage entrepreneurial ideas in the community.In July 2010, Sensis made a permanent downsize to remove 84 jobs, and it was announced in July 2011 that Swedish defense company Saab AB had signed a deal to purchase Sensis for $155 million.In January 2014 30 people were made redundant from the company's air traffic management business. Ten months later Sensis' president, Ken Kaminski, resigned. It was also announced that there would be a further 27 job losses. Sensis cited a challenging business environment for both rounds of layoffs. Wikipedia.

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A method of aircraft navigation via receiving signals emitted by other aircraft and corresponding reply message transmitted by ground transceivers and the using a new diverse-ranging algorithm that solves for the positions of a eavesdropping aircraft and the positions of direct-reply aircraft emitting the signals received by the eavesdropping aircraft.


A light-weight, air-cooled transmit/receive unit is provided, including a first external cover member, an opposed second external cover member, and a central housing unit, including thermal management means, interposed between the first and second external cover members. A transmit/receive circuit board, including components and an integrated and common radiating element for at least one channel, is interposed between a first surface of the central housing unit and the first external cover member, and a controller circuit board and a power converter circuit board are interposed between an opposed second surface of the central housing unit and the second external cover member.


The system and method of the present invention provides a mobile node (e.g., target), such as an aircraft, vehicle or mobile piece of equipment, the ability to determine its own position by passively listening to wireless time synchronization communications, such as IEEE 1588 Precision Time Protocol (PTP) messages, exchanged between nodes over a wireless network.


The present invention utilizes the existing DME transponder system infrastructure to augment existing ground surveillance multilateration (MLAT) capabilities by providing additional measurements for determining the position of an aircraft equipped with a DME transponder. DME listeners receive DME interrogation signals and DME reply signals, determine TDOA between the DME transponder and each DME listener, and transmit data to a central computer that clusters TDOAs between the DME transponder and the DME listeners and computes the aircraft position using the clustered TDOAs. The DME-aided MLAT can be used as a backup surveillance system when GNSS-based systems are unavailable. The DME-aided MLAT can be integrated with SSR receive units (RUs) performing multilateration (MLAT) calculations.


The present invention provides a system and method for aircraft to determine own position and navigate using a navigation heartbeat signal broadcast on a DME uplink and/or a Mode-S uplink frequency. The present invention enables deep integration between the existing navigation systems (DME interrogation-reply ranges and GPS/WAAS raw TDOA or pseudo range measurements) and the DME heartbeat TDOAs or Mode-S heartbeat TDOAs to provide a highly accurate navigation positioning capability and provide necessary backup capability in lieu of GPS to maintain the necessary RNP/RNAV capability and avoid degrading aircraft operational safety.


A system and method of data correlation and analysis of past activities and prediction of future activity that includes establishing a database comprising structured metadata on at least one computer and a distributed system of networked computers having a plurality of access levels, configuring a database front-end to parse incoming data, the database front-end defining a plurality of entities and events, each having one or more attributes, and correlation IDs, which are user defined attribute relationships that correlate events and entities, collecting data, parsing the incoming data in the database front-end into structured metadata, the distributed analysis engine correlating the incoming structured metadata with structured metadata in the database and determining micro-patterns in the structured metadata, generating a graphical representation of a composite network of the determined micro-patterns as super-objects, and predicting future activity from the one or more super-objects representing the determined micro-patterns.


Patent
Sensis Corporation | Date: 2011-11-16

The present invention is a corpsman/medic medical assistant system that includes a portable transmit/receive pack, sensor leads for first and second physiological sensor subsystems and a corpsman/medic medical assistant control unit that includes a wireless transceiver. The portable transmit/receive pack has a sealed housing that includes the first and second physiological sensor subsystems, at least one processor running at least one algorithm, a wireless transceiver, and memory with a front panel that includes a display, at least one event key, a treatment button for recording treatment data, a timer, an observation button for recording observation data, and a plurality of physiological trend indicators. The algorithm determines a current physiological trend status of the patient based on the plurality of physiological measurements, and the transmit/receive pack links to the control unit by the wireless transceiver and receives the current physiological trend status of the patient.


A system and method for an arrayed sensor to resolve ambiguity in received signals, improve direction of arrival accuracy and estimate a location of one or more targets in an environment including signal interference.


A method using airport surveillance data to output a location of a delay and an amount of time a vehicle is subjected to the delay during a movement of the vehicle between two locations, the delays being observed in the surveillance data as a knot of several data points. A first method is used to identify proposed knots based on distances between individual data points within the data. A second method is used to identify proposed knots based on the speed of the vehicle. Another method can be used to separate proposed knots have been incorrectly joined together. This method performs the separation by arranging the data points into a two-dimensional grid to form clusters of grid cells having data points. The location of the individual cells is then analyzed to determine whether clusters should be separated. Each of the remaining clusters defines a hold where the vehicle is delayed.


A method of using airport surveillance data to determine a location of a delay and an amount of time a vehicle is subjected to the delay during a movement of the vehicle between locations including obtaining a time-ordered sequence of data points representing the movement of the vehicle, creating a speed vector (sv) for each data point, replacing ground speed elements in the speed vector (sv) with a one when the ground speed element is less than a speed threshold, performing a spatial density test on each data point in a sequence of consecutive one entries, defining a starting and stopping index for a consecutive sequence of data points as a preliminary hold, determining whether to merge adjacent preliminary holds, determining a time duration of each preliminary hold and eliminating any preliminary hold having a time duration less than a predetermined time duration and outputting the results.

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