An MTRC-AHP Compensation Algorithm for Bi-ISAR Imaging of Space Targets

Journal of Environmental and Public Health

Liú

et al. 2022

The ecological problems faced by China’s environmental protection are becoming more and more serious. Serious haze occurs frequently in some areas. Water pollution, soil pollution, and other new types of pollution are still relatively prominent problems. Therefore, rural architectural planning and landscape optimization design should be based on the premise of ecological environmental protection. This paper puts forward the evaluation of rural architectural planning and landscape in the context of ecological environment protection and uses the analytic hierarchy process to analyze and obtain the evaluation results. This method has a comprehensive and scientific powerful evaluation function. The experimental results of this paper show that after the evaluation of the analytic hierarchy process, it is found that the comprehensive score of the architectural planning and landscape of village A is not very high. The highest weight is 0.3210, the landscape diversity score of street A is 1.28, and the landscape diversity score of street D is 1.76. This is the highest score, indicating that the architectural planning and landscape of the village cannot meet the needs of contemporary ecological environmental protection. Aiming at the problems existing in the landscape, the corresponding measures are also given at the end of the experiment, which has certain significance for the landscape optimization design.

Section: Architectural Planning and Landscape Evaluation Based On Ahpmentioning

confidence: 99%

[Retracted] Rural Architectural Planning and Landscape Optimization Design under the Background of Ecological Environment Protection

Wei

Journal of Environmental and Public Health

Liú

et al. 2022

“…Here,

B_{f}

represents the Doppler variation, which is the bandwidth of the time‐variant Doppler due to the high‐order phase terms, during the coherent processing interval. As analysed in [30], the phase spectrum of quadratic and quartic phase terms has a higher influence on interferometric imaging than cubic and quintic phase terms. However, the cubic and quintic phase terms have a greater influence on the PSLR of the scattering point and unwanted Doppler offset, which is measured by the Doppler resolution

Δ f_{d} = 1 / T

.…”

Section: Mie Series Theory and Polarisation Variation Computationmentioning

confidence: 99%

“…Here, the unwanted Doppler frequency offset of the main‐lobe of a scatterer is the Doppler offset induced by the high‐order phase term, which will result in transverse calibration error of scattering points in the ISAR imaging process. For the convenience of readers, we have provided the phase error of quadratic and quartic phase terms as well as PSLR and Doppler offset of cubic and quintic phase terms with respect to

D

values in Figure 4 as done in [30]. Figure 4(a) and (b) ndepict the phase error at the peak point changing with

D

values.…”

Section: Mie Series Theory and Polarisation Variation Computationmentioning

confidence: 99%

“…By denoting

φ

as the phase of the main‐lobe peak of a PEC sphere, the high‐order phase term can be expressed as follows:

φ_{i} = \exp (- j π μ_{i} t_{n}^{i}) (i = 2, 3, 4, 5), - \frac{T}{2} \leq t_{n} \leq \frac{T}{2}

where

T

represents the coherent processing time. To measure the influence of different order phase terms on the Bi‐ISAR imaging system,

D = T \cdot B_{f}

, which represents the time‐bandwidth product of a certain order phase signal, is analysed in [30]. Here,

B_{f}

represents the Doppler variation, which is the bandwidth of the time‐variant Doppler due to the high‐order phase terms, during the coherent processing interval.…”

Section: Mie Series Theory and Polarisation Variation Computationmentioning

confidence: 99%

See 1 more Smart Citation

Polarisation variation of linear polarised Bi‐ISAR system in space targets imaging

2021

IET Radar Sonar & Navi

Self Cite

A bistatic inverse synthetic aperture radar (Bi-ISAR) system is used to observe space targets through different viewing angles via a bistatic radar configuration. It is seen that the receiver of a linear polarised Bi-ISAR system with a long baseline will encounter energy variation and high-order phase deviation in ISAR imaging due to the polarisation variation of this system. Here, the authors quantitatively analyse the energy variation caused by polarisation mismatch in a linearly polarised Bi-ISAR system by investigating the time-varying bistatic angle and intrinsic variable polarisation effect of targets via the combination of observation geometry and computational electromagnetic. The highorder phase deviation in long-term coherent processing is also presented through the same strategy. The authors conducted simulations for a bistatic system, which is configured with different baseline vectors, to analyse the impact of polarisation variation of the linear polarised Bi-ISAR system on the energy loss and high-order phase terms.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

“…Moreover, the scatterer defocus model derived based on the POSP [15] fails when the time–bandwidth product of the residual quadratic phase is small. Additionally, there exists a large scatterer defocus in the azimuth dimension owing to the spatial variant imaging plane of space targets in ISAR imaging, even if the non‐uniform rotation of the target is accurately compensated by the high‐order keystone transform [20]. Because of the height differences of the scatterers, the defocussing of each scatterer is independent of the others and thus cannot be compensated simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Parametric scatterer extraction method for space‐target inverse synthetic aperture radar image CLEAN

Zhang

Cui

et al. 2023

IET Radar Sonar & Navi

Self Cite

Owing to the time variance of the inverse synthetic aperture radar (ISAR) imaging plane of space targets, scatterers with large heights relative to the imaging plane migrate through several Doppler cells. This defocussing in the azimuth direction of each scatterer cannot be compensated via the traditional migration through the resolution cell (MTRC) compensation method because the height of each scatterer is quite different and independently distributed in the ISAR image. In this study, a parametric azimuth-defocussing model-based CLEAN method is proposed for the space-target ISAR image. First, highorder defocus parameters and their influences on the image of space targets were analysed at different arc segments. Subsequently, a mathematical azimuth-defocussing expression of the ISAR image scatterers was derived after MTRC and azimuth high-order phase compensation, and an approximate defocus expression based on the Fresnel integral was provided for computational efficiency. This model can estimate the complex amplitude, coordinates and defocus parameters of each scatterer in the image domain by applying a sequential quadratic programing algorithm. Finally, the validity and stability of the proposed algorithm for the isolated and coupled scatterer extraction were verified at different signal-to-noise ratios, and different defocus parameters were verified through simulations. K E Y W O R D Sinverse synthetic aperture radar (ISAR), parameter estimation, radar imaging, radar resolution | INTRODUCTIONAn inverse synthetic aperture radar (ISAR) uses a synthetic aperture formed by the relative rotation between the target and radar to obtain a high-resolution image of the target. Owing to its all-weather imaging capability, it has been widely used in military and civilian fields. To improve the imaging quality or extract more information, spatially variant apodisation [1-3], relaxation (RELAX) [4][5][6][7], and other methods are commonly used to enhance images.The CLEAN algorithm was first proposed by astronomers [8] and was later adopted in radar imaging to reduce the interference of sidelobes and speckle artefacts [9]. In recent years, the CLEAN algorithm has been widely used in ISAR imaging. As a deconvolution signal-processing technique, the CLEAN algorithm is usually used for feature extraction of all scatterers in an image [10], wherein it iteratively estimates the point-spread function (PSF) of the strongest scatterer and subtracts it from the image. The PSF of the scatterers can be assumed to be an ideal two-dimensional (2D) sinc function when its high-order phase has been compensated. However, this assumption fails in many realistic scenarios. An accurate PSF mathematical expression model is a prerequisite for fast and successful implementation of the CLEAN algorithm. Owing to the differences in imaging targets, pre-processing methods and processing domains in which the CLEAN method is executed, PSF model variations exist [11][12][13][14][15][16][17][18][19]. The CLEAN algorithm in Ref. [11] extracts parameters ...