Implementation of data interpolation for reducing data points with frequency content preservation in narrowband detection displays

Representation of data points on displays is one of the trickiest part regarding underwater surveillance systems. The data points are mostly large in numbers than the number of pixels to represent them on displays. This makes the data processing domain more interesting to correctly map these data points on displays. The biggest challenge while reducing these data points is preservation of correct information. Mostly simple averaging and linear mapping do not ensure correct content preservation. The content preservation is guaranteed by the use of more complex mathematical techniques such as quadratic equations, sum of trigonometric functions etc. These complex mathematical techniques certainly ensure correct preservation of data while reducing its size for mapping it on displays. One of the well-known data fitting techniques is “Spline Interpolation”. This technique guarantees correct representation of data points and uses 4th order quadratic equations to correctly deal with data points. The use of quadratic equations makes it heavy on processing end in terms of real time processing constraints. In this context there is a need to have some technique that not only reduces data points correctly but also keeps in view the timing constraints of real time operation. This paper presents a novel technique that meets all the real time processing constraints and keeps the integrity of data intact. This technique can reduce data points up to hundreds of times with correct preservation of data content and frequency information. This technique has been tested on several different scenarios of narrowband detection displays and provided good results. These results clearly show the robustness and accuracy of the proposed technique in comparison to other technique like “Spline Interpolation”.