A.A. Potapov

The article describes author's novel prompt method of low-frequency magnetic field's nonlinear variations assessment along typical pedestrian ways; this variations are caused by field's numerous spatial heterogeneities. The method is based upon functional combining of wideband low-frequency gaussmeter (30-2 000 Hz), GPS receiver and geographic information systems software; high rate of spatially distributed data acquisition is achieved by taking measurements in motion. The methods of data merging from various utilized experimental instruments and the experimental results processing technique are presented. The latter include algorithms of magnetic field's local gradient estimation, average magnetic field's profile portion length computation (the portion is used for gradient assessment) and the probability of user defined magnetic field's reference levels violation. The paper also presents the experimental results visualization technique in geographic information systems (GIS) environment. The results of low-frequency magnetic field's nonlinear variations experimental assessment in the frequency range of 30-2 000 Hz along five urban profiles of 11,3 km total length along avenues with dense traffic and pathways in residential areas are presented. The profiles include 6 590 measurement points with spatial resolution of 1,4-1,8 meters. It's shown, that along experimental profiles field variations lay between 10-15 and 30-40 dB along track parts with length below 100 meters; typical local field gradients comprise from 1-2 to 4-6 dB/m, i.e. in urban environment a pedestrian undergoes high-level nonlinear amplitude variations of low-frequency magnetic fields. It's exposed, that the probability of 0,25 µT reference level violation equals 0,47 for all experimental dataset and varies between 0,20 and 0,69 for certain profiles; this fact proves considerable abundance of potentially harmful magnetic field levels in modern city environment and shows the necessity of subsequent research in power-frequency fields monitoring methods. With received experimental data as an example (in an area with numerous multistoried buildings) the ways of 3D visualization optimization by using appropriate capabilities of GIS ArcGIS software are discussed