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 fine-tuning 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. 1.0 INTRODUCTION This paper discusses a method for computing seismic attenuation using a single sensor and a single vehicle, usually tracked. Such physical behavior is important because many classification schemes are either frequency based, or are time-frequency based decompositions of the signal collected at the sensor. Misclassification of vehicles can happen at large distances away from the closest point of approach (CPA). The reason for this is due to the vehicle traveling at different speeds; here for tracked vehicles, tread slap (to be discussed more fully below) changes the peak frequency of the seismic power spectra. Other mechanical attributes of a motorized vehicle that are speed dependent also contribute to changing a vehicle’s power spectra; not taking these into account can also result in misclassification. However if we concentrate on the case where a tracked or wheeled vehicle moves at a constant speed towards, past and away from CPA, then we still observe classification that is a consistent function of distance as well as frequency [1, 2]. The origin of this behavior is seismic attenuation. It is well known that the ground acts as a lowpass filter. High frequency seismic energy from a tracked or wheeled vehicle will not travel as far as energy with low frequency content. The attenuation will be different for various soil, rock, and surface types. 1 Knowledge of seismic attenuation is useful in that this gives some idea of the range of a vehicle, especially a tracked one as a function of speed. As spectral information from fast vehicles is here peaked at higher frequencies than with slower vehicles, seismic attenuation will reduce the energy from these faster vehicles at a farther distance. The views and conclusions contained in this document are those of the authors and should not be interpreted as presenting the official policies, either expressed or implied of the Army Research Laboratory or the U. S. Government. Approved for public release; distribution is unlimited.