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This study has utilized the advantages of inertial sensors and complementary filter to estimate the motions and attitudes. Although the progress in micro-electro-mechanical systems has improved the qualities of the inertial sensors, including accelerometers and gyroscopes, their bandwidths limits them from accurate measurements and applications. However, by properly using the complementary filter, the signals can be adopted to generate reliable data for positioning. To obtain the best results, the frequency response and transfer of sensors are identified and the cut-off frequency of complementary filter is defined accordingly. To minimize the measurement error caused by the external forces and disturbances, a state estimator has been integrated into the system. To validate the real-time performance of this system, tests are conducted on linear and rotating platforms. The estimated data shows the functionality of this developed complementary filter to blend the high-frequency measurements of gyroscopes and low-frequency ones of accelerometers to generate trustworthy positioning information.