In this contribution, we propose a new filtering and denoising technique for one-dimentional signals based on the nonlinear quadratic Teager-Kaiser operator. This technique is a threshold ‘energy’ based approach where outliers are first detected and then replaced by their estimated values. The proposed technique performs better compared to the alpha-trimmed and running mean filter, also with moderate complexity. In particular, we present an application of the proposed real-time filtering approach for postprocessing the measurements of time delay signals in a mobile positioning system highly affected by the propagation environment.