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Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

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712 CHAPTER 16 Human Detection With <strong>Radar</strong>: Dismount DetectionFIGURE 16-1Illustration <strong>of</strong>transmitted pulsedDoppler chirp signaland key parameterdefinitions.FrequencyBandwidth = γτf 0τ TimeAmplitudeτT 2T 3T ttˆ tˆ tˆhuman targets the principle <strong>of</strong> superposition is valid. Moreover, work by Van Dorp [51] hasshown that by (1) dividing the human body into just 12 parts, (2) modeling each part as apoint target, and (3) summing the responses, a mathematical model for the human responsethat matches remarkably well with measured spectrogram data can be produced. Thus, amathematical approximation to the human radar return may be written from (16.1) asK∑( ) ˆt − t d,is h (n,t) = a t,i rect e j[−2π f ct d,i +πγ(ˆt−t d,i ) 2 ](16.3)τi=1where K is the total number <strong>of</strong> parts into which the body is divided, and i is an indexreferring to each body part (1 ≤ i ≤ K ). Embedded within this equation are two factorsthat are directly impacted by human modeling: the time-varying range R i <strong>of</strong> each bodypart to the radar (in t d,i = 2R i /c), and RCS <strong>of</strong> each component (i.e., the factor σ in a t,i ).16.2.2 Human Kinematic ModelsResearchers have pursued a variety <strong>of</strong> approaches in modeling human kinematics, most<strong>of</strong> which revolve around decomposing the human body into a finite number <strong>of</strong> parts andcomputing the time-varying range for each part using kinematic models. An alternativeapproach has been taken by R. G. Raj, who has pointed out that in many cases humanactivity occurs in real-time unconstrained environments, where the type <strong>of</strong> activity ormodel parameters are not known a priori, leading to a mismatch between the true activityand motion model used. Thus, Raj proposed directly modeling and classifying the timefrequencymotion curves using a Gaussian g-snake model [62, 63].Nevertheless, kinematic models have provided valuable insight and utility in the detectionand identification <strong>of</strong> dismounts and remain the most widely explored approachtoday. For example, He [64] recently proposed a modified version <strong>of</strong> the linear-rigidmodel developed by Zhang [65] in which the head and torso were modeled as a singlepoint scatterer, the arms as independent cylinders, and the legs as two interconnectedcylinders. The periodic arm motion was modeled as being that <strong>of</strong> a pendulum, while theleg motion was modeled by a combination <strong>of</strong> vibrations and rotations.

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