Target Localization Utilizing the Success Rate in Infrared Pattern Recognition

The architecture of an indoor target localization system employing a small number of infrared-emitting diodes and sensors is presented in this paper. The properties of infrared light and magnetic fields have already been exploited for position localization in distances of several centimeters. Ultrasonic waves and laser light can be used for longer distance estimation if the system is capable of accurately measuring the time of flight of the reflected signals. The proposed approach intends to cover a distance of several meters without requiring high accuracy measurements and sensors of increased precision. The digital infrared patterns that are transmitted from a constant position are recognized by a pair of sensors mounted on the moving target, with varying success rate depending on the distance and the angular displacement from the transmitter. Processing the success rate instead of the analogue signal intensity requires low-cost digital microcontroller systems of moderate precision and computational power. Moreover, longer distances can be covered since attenuated, noisy, or scrambled patterns are also important for the position estimation in the proposed approach. A proper modeling of the pattern recognition success rate is presented in order to estimate distances of several meters with an adjustable estimation error. The use of multiple infrared pattern transmitting devices results in extension of the area covered and a reduction of the estimation error due to additional crosschecks that may be accomplished. The area covered can be increased by a factor between 20% and 100% depending on the allowed range overlapping of the transmitting devices. The potential topology of these devices is also discussed and analyzed. The presented system can be used in several virtual reality and robotics applications