Least Square Method
The passive range estimation technique can be represented in vector space as the problem of estimation of motion parameters P using a known bearing-only vector R and plane position S. The solution depends largely on the target dynamics. There are three most important types of target dynamics for this problem: almost motionless (stationary) targets, targets moving rectilinearly, free-moving targets (with rapidly changing speed and/or direction). Testing of chosen minimization functions on modeled data gives an accuracy of the passive range estimation technique not worse than 10%, while in some cases 1% or less. Testing on records of real flights gives an accuracy in passive range estimation about 30% for a free-moving target, such as an aircraft. The passive range estimation technique allows estimating of range that is well above the range of the laser rangefinder and reaching the detection ability limit of an optical radar station. This technique also allows estimating of the target aspect angle using the target velocity vector. The requirements for the aircraft navigation system are formulated for improving the quality of the passive range estimation technique.