A Revisitation of the Phenomenological Approach with Applications to Radar Target Decomposition

Huynen, J. Richard

doi:10.21236/ada116390

Cited by 16 publications

(12 citation statements)

References 3 publications

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“…The persistence-optimized Euler parameters were combined into a consolidated score s according to Eq. (6). In this equation, sm, for example, is the correlation score between the unknown vehicle and the library vehicle when they are both imaged in Euler parameter m space.…”

Section: Atr Performance Resultsmentioning

confidence: 99%

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Development and assessment of a complete ATR algorithm based on ISAR Euler imagery

2007

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The Euler decomposition, when applied to the polarization scattering matrix, attempts to extract phenomenological information about the scattering target. Because the Euler parameters constitute a more physically relevant set of parameters than the traditional HH-VV ISAR representations, they have potential to improve ATR performance. The Euler parameter's usefulness in target recognition, however, is effected by several layers of signature variability. Unfortunately, many of the variability layers are often omitted in a typical ATR study. A complete ATR algorithm was therefore developed that allows for all layers of variability and requires no previous knowledge of the target's position, orientation, or average reflectivity. The complete ATR algorithm was then used to assess the effectiveness of Euler ISAR imagery in target recognition when all layers of variability are considered. The general approach and sub-methods used to construct the complete ATR system will be presented, including the methods to determine the targets orientation, registration, and to compare it to a library of pre-rendered target images. Finally, the performance of the Euler parameters in target recognition using the complete ATR algorithm will be presented.

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Section: Atr Performance Resultsmentioning

confidence: 99%

“…(2), and the Euler parameters are extracted one by one. The detailed derivation of the Euler transform equations has been presented previously 5,6 .…”

Section: S D =Umentioning

confidence: 99%

Development and assessment of a complete ATR algorithm based on ISAR Euler imagery

2007

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“…By analyzing the various plots for the two principal target categories considered, we are able to verify the fundamental theorems which can be derived from Huynen's polarization fork concept (Huynen, 1960(Huynen, , 1970(Huynen, , 1978(Huynen, , 1982; the target vector scattering interaction theory (Bennett and Mieras, 1982); the relationship between relative scatterihg mqtrix co-polarization phase and specular point curvature perturbations of Kennaugh's target silhouette area function (Foo, 1982); and the dynamic behavior of the polarization fork motlon (Poelman, 1980(Poelman, -1982. Although, we have considered here the monochromatic (CW) backscattering case for reciprocal symmetrical targets only, it is evident that very definite target polarization properties exist which may be utilized as target characteristics classifiers and Identifiers.…”

Section: 3mentioning

confidence: 96%

“…Althouth It still requires extensive extension, it clearly paves the single unique method of complete polarimetric description of radar clutter and average object, an immensely complicated electromagnetic inverse problem. We are fortunate to have the senior expert In the field, Dr. J. Richard Huynen (1982), join the efforts of this research task, and in a separate report entitled, "A revisitation of the phenomenological approaches with app'lication to radar target decomposition", he has further developed on his N-target decomposition theory.…”

Section: Vector Scattering Center Interactionmentioning

confidence: 99%

“…Here we reproduce Figure 5 of (Morgan and Weisbrod, 1932) in Figure 20, which is being explained and interpreted in There exists one major problem in applying polarimetric techniqdes derived from the optimal targct polarization tiieory to the polarimetric transient time-dependent problem of ramp response target cross-sectional area projection shape reconstruction, because this optimal polarization target null theory is derived In the frequency only as a mono-frequency theory. Both Kennaugh (1949 and Huynen (1960Huynen ( , 1970Huynen ( , 1978Huynen ( , 1982 were aware of this complication in their pioneering and continuing research efforts of advancing the stateof-the-art in radar target polarimetry. What we urgently need is a thnedependent polarization-senitive target feature descriptive theory which is still not completely available.…”

Section: Observationsmentioning

confidence: 99%

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Basic Concepts of Radar Polarimetry and Its Applications to Target Discrimination, Classification, Imaging and Identification

Boerner¹

1982

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Polarizai:ion, radar polarimetry, target discrimination, classification, imaging, optimal polarization nulls, polarization transformation matrix, Mu.eller matrix, radar scattering ,%atrix, polarization fork.1;1-0. ASSTR ACT (Continue on rova. old. It A4 -at *orny and Odonaltli by block "Wob".1IInI meticulous detail, a su~cinct sunimary of basic electromagnetic wave polarization descriptors, of' the various scatterer polarization transformation and of the scatterer descriptive operators is introduced. It is then shown how 'the five (5) independeutt ma\vrix parameter for the relative phase monostati-scattering matrix de~scrib.'ng an isolated, yet regionally distributed, target in a reciprocal propagatiov medium can be recovered from (i) amplitude-. only, (ii) mixed amplitude plus pai'tial phase, (iii) complete two-step (Cont'd) 20.ABSTRACT amplitude-phase measurements. Basic properties of the radar target scattering matrix for linear (H, V) and circular (R, L) polarization basis Pre described in terms of geometrical target features as functions of the specular point surface coordinate parameters, known as gaussian principal, main and related curvature functions.Based upon this succinct background introduction on radar polarimetry, the concepts are applied mainly for the coherent case to various classes of increasing order of sophistication, as defined in detail in the INTRODUCTION, to the problem of radar target handling for the noa-cooperative, limited-data case. ff.j- ABSTMRCTIn meticulous detail, a succinct summary of b~asic electromagnetic wave polarization deiscriptors, of the various scatterer polarization transformation matrces, and its Invariants of the associated optimal matrix polarizatlkons, ane of' the scatterer descriptive operators In Introduced, It Is then show~n holmw thf. five (5) Ir-dependent matrix parametr~r for the relat~iv% phase mora-static .iattcring matrix. cescrlbing an~ Isolated, ;et relilonally dls'ributud, t.arget In a revciprocal prdIpagt,.tion medium can be/#rer~overed from (1) amplituda-only, 01i) minxed ainpiltu(ce pium~ partial phase., (il1) c;omplete t-wc-ate,ý a3;Pplltude-I phetse roIeasure~menti", Ba,,ic prope'rti-es of the radiar target catri:g matrix forĩ llnear' (H, V) and r'1rcular (R, L) polarrizva.tion basis are desccrbe~d in terms o"'. cttimetrical 1argetdie,-tures as functions of the specular polr-. 5.urface coordin~ate parameters, Vnown ill gausslao principal, main and related cuivature functlor),. Based upon this suci:inct background Introduction on radar polarimetry, the concepts-are applie.d mainly fur thie zoherent case to variou~j classes of 7rncreas-Ing order of sophistication, as defined In detail In the 1147KODUCTIONi, 4o the problem of radar target handling~ for the non-ccaperative, ilimited-dat'A case.l.

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CommSense: a communication infrastructure based sensing instrument for environment monitoring

Sardar

Mishra

Khan

2019

CSIT

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A Revisitation of the Phenomenological Approach with Applications to Radar Target Decomposition

Abstract: COMMUNICATIONS LABORATORY 0DEOepart-eot of information Engineerlng

Cited by 16 publications

References 3 publications

Development and assessment of a complete ATR algorithm based on ISAR Euler imagery

Development and assessment of a complete ATR algorithm based on ISAR Euler imagery

Basic Concepts of Radar Polarimetry and Its Applications to Target Discrimination, Classification, Imaging and Identification

CommSense: a communication infrastructure based sensing instrument for environment monitoring

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