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Advanced Target Tracking Techniques

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In many engineering applications, including surveillance, guidance, or navigation, single stand-alone sensors or sensor networks are used for collecting information on time varying quantities of interest, such as kinematical characteristics and measured attributes of moving or stationary objects of interest e.g. maneuvering air targets, ground moving vehicles, or stationary movers such as a rotating antennas. More strictly speaking, in these applications the state vectors of stochastically moving objects are to be estimated from a series of sensor data sets, also called scans or data frames. The individual measurements are produced by the sensors at discrete instants of time, being referred to as scan or frame time, target revisit time, or data innovation time. These output data sensor reports, observations, returns, hits, plots typically result from complex estimation procedures themselves characterizing particular waveform parameters of the received sensor signals signal processing. In case of moving point-source objects or small extended objects, i.e. typical radar targets, often relatively simple statistical models can be derived from basic physical laws describing their temporal behavior and thus defining the underlying dynamical system. In addition, appropriate sensor models are available or can be constructed, which characterize the statistical properties of the produced sensor data sufficiently correct. As an introduction to advanced target tracking techniques characteristic problems occurring in typical radar applications are presented key ideas relevant for their solution are discussed.

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  • Target Direction, Range and Position Finding

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