Seismic attenuation characterization using tracked vehicles

Target classification is one of the most important issues in battlefield situational awareness. As seismic signals are an effective means of obtaining such information any knowledge of the subsurface environment in which the target signal propagates is very important in either developing or finetuning classification algorithms. Seismic signal attenuation is an essential subsurface environmental characteristic and is known to be frequency dependent. We first describe a simple method for computing seismic attenuation using a single seismic measuring device and a large tracked vehicle with known tread spacing characteristics. Following this we extend the method to an array of randomly placed sensor nodes. We first illustrate this method for a single node by means of tracking the size of certain spectral features in measured seismic data. For example the seismic signature of an M60 tank has a distinct peak at a specific frequency depending on its speed. Given the distance to CPA and the vehicle speed a portion of the signal corresponding to a given distance from vehicle to sensor can be examined and the power spectral density of that peak measured corresponding to that distance. From this type of data attenuation profiles can be measured as a function of distance for various frequencies. Seismic attenuation parameters can be computed from the profiles using suitable regression techniques. Data collected for sensor arrays will be analyzed and compared with the single sensor results to assess local ground effects. Also we will compare the ability of an array of sensors to characterize the ground using an impulsive source with the moving vehicle source. This then characterizes the seismic medium and can assist in classification of general targets.