Accurate indoor localization is vital for smart applications, but least-squares quadrilateral (LSQ) degrades under high geometric dilution of precision (GDOP). We propose a constrained least-squares quadrilateral (CLSQ) algorithm that introduces a range constraint from four distance measurements to enhance robustness. Simulations show CLSQ reduces localization error by about 24% compared with LST and maintains stability under varying geometries and noise, making it suitable for practical IoT scenarios.

internet of things,Ultrawideband,least-square,range constraint