rangeestimation

Range estimation is the process of determining the distance between a sensing location and a target or feature. It is fundamental in fields such as surveying, navigation, robotics, astronomy, and telecommunications, and supports tasks from mapping and obstacle avoidance to positioning and alignment.

Common methods include time-of-flight, phase-based, and geometric techniques. Time-of-flight methods measure how long a signal takes to travel to the target and back, multiplying by the propagation speed (for example, light for radar and lidar, or sound for sonar). Phase-based methods use the phase difference of a modulated carrier to infer range, often with a known ambiguity that must be resolved by additional measurements or frequencies. Geometric methods rely on angles or known reference positions: triangulation uses angle measurements from two or more known points, while trilateration and multilateration use measured distances from multiple fixed references to determine the target’s location. Global navigation satellite systems provide ranging information through pseudorange measurements to satellites, solved together with receiver position and clock biases. Visual methods, such as stereo vision and depth from focus or defocus, estimate range from image data.

Applications span autonomous vehicles, aviation, maritime navigation, robotics, surveying, mapping, and astronomy. Key challenges include clock synchronization, signal propagation effects, multipath interference, atmospheric conditions, and geometric dilution of precision. Accuracy depends on sensor quality, calibration, environmental conditions, and the numerical methods used to fuse measurements. Range estimation is frequently integrated with state estimation techniques, such as Kalman or particle filters, to track moving targets and reduce uncertainty over time.