Error analysis of real-time acoustic maps for Dynamap

In this work we evaluate the mean statistical errors incurred within the real-time noise mapping of Dynamap for the equivalent noise levels of each acoustic map. In order to estimate the total error we rely on the Central Limit Theorem which asserts that for the sum of N uncorrelated random processes the total variance of the sum, σ2N, is given by the sum of the individual variances. In the present case, we have identified four processes whose fluctuations contribute to the total variance (error), which denote as σ2T, yielding the result σ2T== σ2pred+ σ2state+ σ2comp+ σ2sample, corresponding to the intrinsic prediction error of the method, σ2pred, the statistical variance of the equivalent noise levels measured by the monitoring stations, σ2stat, the different cluster compositions for different time intervals, σ2comp, and the variance due to stratified sampling, σ2sample. The overall mean error is expected to be bounded by about (1-3) dB.