In order to improve the accuracy of sensor measuring soil moisture, Improved Particle Swarm Optimization(IPSO) algorithm is proposed. Firstly, Gauss transform is utilized to improve the local search ability, and Cauchy transform is adopted to attract other particles to better search space area, which improves the global search ability. Secondly, Chaotic function is adjusted the inertia weight dynamically, it has larger value in the initial iteration stage and smaller value in the later iteration stage, and the searching speed is slowed down in the later iteration. The simulation results show that the Mean Square Error(MSE) and Pearson correlation coefficients of IPSO algorithm are better than that of other algorithms for measuring gravel dehumidification and moisture absorption data, the MSE of the measured data of dehumidification for IPSO at the substrate potential of 1 000 cm is 16.62×10-6, which is 75.59%, 66.67%, 63.53%, 53.73% and 57.53% lower than that for LSM, FOA, HSA, PSO and SAA respectively. For the measured data of moisture absorption at the substrate potential of 1 000 cm, MSE of IPSO is 10.21×10-6, which is 81.42%, 75.29%, 72.00%, 65.57% and 67.69% lower than that of LSM, FOA, HSA, PSO and SAA respectively.