A simple approach of range-based positioning with low computational complexity

For range based positioning the least square (LS) criterion and its produced solution exhibit superb estimation performance, but generally at a very high computational complexity. In this letter we consider the issue how to approach such LS solution in estimation performance at low computational complexity. We propose a novel algorithm that is based on the equations linearized from range measurement equations and implements a weighted least square criterion in a computationally efficient way. The proposed algorithm involves a quadratic equation linking the linearization-caused extra variable and the position to be estimated, thus results in a closed form solution.We analyze and simulate its estimation performance, and evidently show that the proposed algorithm can very closely approach the LS solution in estimation performance at a significantly low computational complexity.