In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing new data points within the range of a discrete set of known data points.
A closely related problem is the approximation of a complicated function by a simple function. Suppose the formula for some given function is known, but too complicated to evaluate efficiently. A few data points from the original function can be interpolated to produce a simpler function which is still fairly close to the original. The resulting gain in simplicity may outweigh the loss from interpolation error. In higher dimensions: Multivariate interpolation is the interpolation of functions of more than one variable. Methods include bilinear interpolation and bicubic interpolation in two dimensions, and trilinear interpolation in three dimensions. They can be applied to gridded or scattered data.
Methods of interpolation are differing in such properties as: accuracy, cost, number of data points needed, and smoothness of the resulting interpolant function.
In my project I decided to implement numerical method for interpolation missing AIS data of ship which includes linear interpolation, cubic interpolation and an identification mechanism for interpolating the missing AIS data of a ship.
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