Windowing

Introduction

The theoretical requirement for inverse FFT is for the data to extend from zero frequency to infinity. Side lobes appear around a discontinuity because the spectrum is cut off at a finite frequency. Windowing reduces the side lobes by smoothing out the sharp transitions at the beginning and at the end of the frequency sweep. As the side lobes are reduced, the main lobe widens, thereby reducing the resolution.

In situations where a small discontinuity may be close to a large one, side lobe reduction windowing should be used. When distance resolution is critical, Rectangular windowing should be used.

Distance‑to‑PIM Windowing Examples

The types of windowing in order of increasing side lobe reduction are: rectangular, nominal side lobe, low side lobe, and minimum side lobe. Figure: Rectangular Windowing through Figure: Minimum Side Lobe Windowing show examples of these types of windowing.

Rectangular Windowing

Nominal Side Lobe Windowing

Low Side Lobe Windowing

Minimum Side Lobe Windowing