In today's world, where drones, remotely controlled vehicles, aircrafts and other autonomous vehicles have become a common mode of carrying out various operations, the Inertial Measurement Units (IMUs) find themselves playing a very prominent role in the field of navigation. IMUs use a combination of accelerometers, gyroscopes and magnetometers to determine the velocity, orientation and gravitational forces acting on the object, they're mounted upon. The sensor outputs of an IMU are not completely accurate and are coupled with errors. This paper focuses entirely on developing a new calibration method for an IMU. A theory was proposed which required the implementation of analytical operations using the basic sensor error model, eliminating the use of expensive hardware and inaccuracies from approximation methods involved. The IMU is moved by hand and placed in different static positions, and then with the help of analytical algorithms developed, the sensor errors were deduced. The performance of the calibration algorithm developed was tested and verified successfully with a commercially available device.