Data smoothing algorithm

Abstract

The paper describes the development of an algorithm for smoothing ship attitude angle data and the use of a spreadsheet for developing and evaluating the performance of the algorithm. The specific project involved the integration of global positioning system (GPS) (AN/WRN-6) to a ships attitude measurement system (SAMS) on board the USNS Observation Island. The SAMS its an inertial navigation system (INS) or more specific, a modified AN/WSN-5. The data output from the SAMS is used by the ship's radar tracking computer to predict a pointing angle and to drive the radar mount pointing angle to the desired object being tracked. Noise on the angle data will propagate through the track computation and will result in mount servo drive errors to compromise the radar's performance. The stabilization angle data output from the SAMS (level, crosslevel, and azimuth) is considerably better than the specification, but not as good as the existing source of data which was used in the development of the tracking computation. It describes the development of the data smoothing algorithm using what is known about the frequency and amplitude of the noise and ship's motion. The algorithm uses the current data point and previous data as required to predict a current smoothed data point in real time for the radar tracking computation. It also describes how a spreadsheet is used to first characterize the data signal and noise using the statistical and plotting tools available in a spreadsheet program. Secondly, it describes the use of the spreadsheet in development of a simulator which is used to characterize the performance of the data smoothing algorithm. The advantage of this is that it is not necessary to use a ship to exercise every possible condition. >