Accelerometer is one of the integral parts of a navigation system which helps in estimating motion parameters of the vehicle to which it is mounted upon. With wide usage of MEMS based sensors in commercial applications such as gaming industry and mobile robotics, these sensors are required to be calibrated appropriately and in as easy manner as possible. Traditional calibration technique requires the sensor to be taken to the laboratory where it is needed to be manipulated in different orientations. However, owing to the non-availability of costly equipment, infield inertial sensor calibration has gained wide popularity in recent times. In this paper, an attempt has been made to simplify the infield calibration technique by mounting the non-calibrated unit over another calibrated sensor or vice-versa, to yield calibration parameters. The cost function arrived for this sensor to sensor calibration is solved using particle swarm optimization technique and its other variants which modifies PSO's own parameters differently is experimented. The PSO algorithm proposed here incorporates constriction factor along with time varying inertial weight for improved results than the traditional PSO scheme. The calibrated sensor reading is then compared with the data obtained from the reference calibrated sensor unit and provides the corresponding result. © 2017 IEEE.