• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.622-629
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• 2011

In this paper, you can see the structure of data slaving software module that is in use on flight test and result of the test with the slaving. The data slaving software module has many functions, data slaving for various instrumentation systems(instrumentation radars, telemetry systems for missile, aircraft and so on), setting some slaving group for multi-target, communicating with the instrumentation systems in a far away site and sending a specific value as slaving data. This fits the requests for flight test that is being performed and improves performance of the instrumentation systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.50-57
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• 2008

A telemetry ground station has a highly directional, parabolic tracking antenna to receive a weak telemetry signal from a target at a distance. The tracking antenna with narrow beam-width normally uses the auto-track method for the target tracking. This paper presents several issues in the auto-track method and introduces a new tracking method using Self-Slaving technique. Self-Slaving means that the tracking antenna is slaved to not data measured by RADAR but GPS/INS informations received by the telemetry system for pointing. The Self-Slaving method shows good performance in comparison with auto-track method.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.31-39
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• 2014

In KSLV-I launch mission, real-time data from the tracking stations are acquired, processed and distributed by the Mission Control System to the user group who needed to monitor processed data for safety and flight monitoring purposes. The processed trajectory data by the mission control system is sent to each tracking system for target designation in case of tracking failure. Also, the processed data are used for decision making for flight termination when anomalies occur during flight of the launch vehicle. In this paper, we propose the processing mechanism of slaving data which plays a key role of launch vehicle tracking mission. The best position data is selected by predefined logic and current status after every available position data are acquired and pre-processed. And, the slaving data is distributed to each tracking stations through time delay is compensated by extrapolation. For the accurate processing, operation timing of every procesing modules are triggered by time-tick signal(25ms period) which is driven from UTC(Universial Time Coordinates) time. To evaluate the proposed method, we compared slaving data to the position data which received by tracking radar. The experiments show the average difference value is below 0.01 degree.

• Aerospace Engineering and Technology
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• v.10 no.1
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• pp.116-121
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• 2011

The tracking radar systems in NARO space center are used in order to acquire the TSPI (Time, Space, and Position Information) data of the launch vehicle. The tracking radar produce the measurements of tracked targets in the radar-centered coordinate system. When the tracking radar is in the Cartesian/Polar tracking mode, the state vector data is sent in radar-centered Cartesian/Polar coordinate system to RCC. RCC also send the slaving data in Test Range coordinate system to the tracking radar. So, the tracking radars have to transform the slaving data in Test Range coordinate system into in radar-centered coordinate system. In this study, we described the coordinate transformation between radar-centered coordinate system and Test Range coordinated system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.10
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• pp.1012-1019
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• 2010

In this paper, The flight data processing system was designed for multiple target flight test. For flight data processing, multiple target grouping, data fusion processing, and data slaving processing were performed and, as a data fusion filter, centralized, and federated Kalman filters were designed. A centralized kalman filter was modified in order to improve the vehicle's low altitude measurement using radar's SNR and estimation process. From the testing of multiple target missile, it confirmed flight trajectory measurement was improved in low altitude area and the beginning stage of vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1447-1454
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• 2017

The realtime test data topic means that process for the data efficiently from many kinds of measurement device at the test range. There are many measurement devices in test range. The test range require accurate observation and determine on test object. In this realtime test data slaving framework system, the system can produce variety of test informations and all these data also must be transmitted to test information management or display system in realtime. Using RTI DDS(Data Distribution Service) middle ware Ver 5.2, we can product the efficiency of system usability and QoS(Quality of Service) requirements. So the application user enables to concentrate on applications, not middle ware. As the reason, Complex function is provided by the DDS, not the application such as Visualization Software. In this paper, I suggest the realtime test data topic on slaving framework of realtime test data based on DDS at the test range system.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.47-56
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• 2015

In the multi-sensor system, sensor registration errors such as a sensor bias must be corrected so that the individual sensor data are expressed in a common reference frame. If registration process is not properly executed, large tracking errors or formation of multiple track on the same target can be occured. Especially for launch vehicle tracking system, each multiple observation lies on the same reference frame and then fused trajectory can be the best track for slaving data. Hence, this paper describes an on-line bias estimation/correction and asynchronous sensor fusion for launch vehicle tracking. The bias estimation architecture is designed based on pseudo bias measurement which derived from error observation between GPS and radar measurements. Then, asynchronous sensor fusion is adapted to enhance tracking performance.