In proceedings of
SSW 2008, International Workshop on Small Satellites, New Missions And
New Technologies.
05-07 June 2008, Istanbul, TURKEY.
Emerging hardware technologies and modern software development libraries have made it easier to implement advanced techniques for location-aware positioning and information systems. Leveraging these technologies, we designed a GPS- and WLAN-enabled system for location determination in both civil and defense applications.
The proposed system is based on multi-user landmark information that is transmitted to a central coordination system. The collected data are then managed and shared among multiple users, enabling effective tactical navigation and coordinated decision-making.
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The system is designed to operate on portable devices with limited energy resources and processing power. Users interact with a three-dimensional (3D) model of the region of interest. Each user can determine their position in terms of latitude, longitude, and elevation through a direct connection to GPS satellites.
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During the course of this study, we developed two versions of a reference application that served as a testbed for evaluating the proposed system.
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The virtual 3D terrain model consists of a set of coordinate points generated using a 3D modeling application. In the sample implementation, the modeled area covers approximately 120 km × 120 km and is divided into 100 terrain segments arranged in a 10 × 10 grid.
The primary motivation for terrain segmentation is to render smaller portions of the available region at a higher level of detail. Since handheld devices have significantly more limited memory resources than desktop computers, efficient memory utilization is essential.
The sample region represents a relatively small geographical area encompassing southeastern Türkiye, northern Iraq, and southwestern Iran. Loading the entire region into memory is neither practical nor feasible while maintaining an acceptable level of visualization detail.
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Accordingly, the reference application loads only a 48 km × 48 km portion of the terrain into memory at any given time. The amount of terrain data processed for each rendered scene varies dynamically according to the observer's current position and viewing direction.
Because the primary objective of the system is to provide high-resolution elevation data, the terrain representation must be carefully optimized to balance visual fidelity with the limitations imposed by large digital elevation datasets. |
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Each terrain segment is overlaid with satellite imagery, which is used as the texture during rendering to provide a realistic visualization of the terrain.
The resolution and quality of the textures depend on the capabilities of the target mobile platform. The use of satellite imagery significantly enhances users' perception of the terrain by providing visual information that cannot be conveyed by elevation data alone. The total number of terrain segments that can be loaded into the device's memory at any given time is constrained by several factors, including the size of the texture images, the volume of elevation data, the available memory, and the processing capabilities of the mobile device. |
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In the current testbed implementation, each terrain segment is represented by a grid of 51 × 51 elevation points. Consequently, each segment contains 2,601 elevation data points. With a total of 100 terrain segments, the complete 120 km × 120 km region is represented by 260,100 elevation data points.
At runtime, only a subset of the terrain is maintained in the device's dynamic memory. Specifically, a maximum of 4 × 4 (16) terrain segments are loaded simultaneously, limiting the number of elevation data points processed for 3D visualization to 41,616. This significantly reduces memory usage and computational overhead while maintaining an adequate level of visual detail.
The accompanying figures illustrate the complete terrain model composed of 100 segments, as well as the 2,601 elevation data points that constitute a single terrain segment. The latter is presented in both top-down and perspective views to demonstrate the underlying terrain representation.
| Points per Side |
Total Points in a Single Terrain Segment |
Average Number of Points on Viewport |
Average FPS |
Minimum FPS |
Maximum FPS |
|---|---|---|---|---|---|
| 301 | 90,601 | 453,005 | 0.02 | 0.005 | 0.06 |
| 251 | 63,001 | 315,005 | 0.085 | 0.02 | 0.20 |
| 201 | 40,401 | 202,005 | 0.20 | 0.12 | 0.42 |
| 151 | 22,801 | 114,005 | 0.70 | 0.20 | 1.10 |
| 101 | 10,201 | 51,005 | 1.20 | 0.90 | 2.00 |
| 51 | 2,601 | 13,005 | 4.00 | 3.00 | 7.00 |
| Points per Side |
Total Points in a Single Terrain Segment |
Average Number of Points on Viewport |
Average FPS |
Minimum FPS |
Maximum FPS |
|---|---|---|---|---|---|
| 301 | 90,601 | 271,803 | 0.017 | 0.003 | 0.050 |
| 251 | 63,001 | 189,003 | 0.071 | 0.012 | 0.167 |
| 201 | 40,401 | 121,203 | 0.167 | 0.072 | 0.350 |
| 151 | 22,801 | 68,403 | 0.583 | 0.120 | 0.917 |
| 101 | 10,201 | 30,603 | 1.000 | 0.540 | 1.667 |
| 51 | 2,601 | 7,803 | 3.333 | 1.800 | 5.833 |
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Considering a surveillance team as the primary users of the system, the application enables users to place and manage multiple landmarks within a specified operational area. To support this functionality, the system implements a 2D-to-3D unprojection algorithm that determines the three-dimensional coordinates corresponding to a point selected on the two-dimensional touchscreen. Whenever a user touches the display, the system computes the corresponding 3D coordinate, provided that the selected point lies on the terrain surface.
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This project is supported by The Turkish State Planning Organization under “The Next Generation Satellite Networks and Applications” project, No: DPT 2003-K120250