LAUSR

Abstract Desire of inexpensive Electro-Optic and Micro-Electro-Mechanical System (MEMS) inertial sensors has drastically been increased in the recent times for both military and commercial applications. Beside the traditional applications, reduced cost of such sensors has opened new domains in personal navigation. This paper provides a framework for attitude estimation using miniaturized and cost-effective Inertial Measurement Units (IMU). Sensor fusion of gyroscope, accelerometer and True Air Speed (TAS) sensor helps in minimizing the characteristic time growing error present in gyroscopic integrated data. A novel approach of TAS model development is implemented to generate true air speed data in the absence of TAS sensor. The presence of linear acceleration is estimated and eliminated by means of gyroscope and TAS model. Due to the slight difference in two direction vectors, an error function is estimated and constantly compensated by using a Proportional-Integral (PI) block. Coarse tuning of PI gains is applied and simulated results are produced to assess the filter performance by using real vehicle data. It has been presented that the proposed filter can be used to compute a reasonably accurate attitude solution by using low cost inertial sensors when external aiding is unavailable or not useful.