Principles of Modern Radar: Basic principles

Richards, Mark; Scheer, J. A.; Holm, W.

doi:10.1049/sbra021e

Cited by 1,178 publications

(63 citation statements)

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“…The architecture of CA-CFAR is the simplest among the other CFAR processors. Where X1, X2… XN are the samples which are there in reference cells N, G is the guard cells, CUT is the cell under test, The CFAR constant, T , for the CA-CFAR, assuming homogeneous background noise, is giving by [7]:…”

Section: Cell-averaging Cfar Methodsmentioning

confidence: 99%

“…Solving the GO-CFAR constant for a given probability of false alarm is much complex than in the CA-CFAR. To calculate the CFAR constant in the GO-CFAR, numerical techniques is used to solve the given equation [7].…”

Section: Greatest Of Cell-averaging Cfar Methodsmentioning

confidence: 99%

“…Then the estimated average threshold and the CFAR constant are both multiplied together to produce the actual threshold value. Comparator compares the threshold value with the CUT for making decision about the presence or absence of the target [7].This section introduces four types of the standard CFAR processors along with VI-CFAR. The logical architecture of CA, GO, SO CFARs is given by:…”

Section: Architecture Of Cfarmentioning

confidence: 99%

“…3 represents the architecture of the SO-CFAR. Numerically, the CFAR constant of the SO-CFAR can be calculated from the average probability of false alarm as[7]:…”

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confidence: 99%

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Multiple targets detection in the marine environment using matlab

Satyanarayana²,

V.B.K.L³

2018

IJET

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This paper implements multiple targets detection against sea clutter by mathematically modeling target as a single point target and seaclutter as k-distribution model and observing the deterioration in the effective operation of radar using signal processing by matlab. A Variability Index (VI) algorithm is suggested for detection on the basis of constant false-alarm rate (CFAR) property even in heterogeneous conditions. Comparative analysis of VI-CFAR against various CFAR methods (CA, GO, SO, OS) for multiple targets detection in heterogeneous environment is done in this paper. Comparison and evaluation is done by means of the data which is simulated in MATLAB. The logical operation of the method is verified in heterogeneous condition.

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Section: Cell-averaging Cfar Methodsmentioning

confidence: 99%

Section: Greatest Of Cell-averaging Cfar Methodsmentioning

confidence: 99%

Section: Architecture Of Cfarmentioning

confidence: 99%

“…3 represents the architecture of the SO-CFAR. Numerically, the CFAR constant of the SO-CFAR can be calculated from the average probability of false alarm as[7]:…”

mentioning

confidence: 99%

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Multiple targets detection in the marine environment using matlab

Satyanarayana²,

V.B.K.L³

2018

IJET

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“…When the searching velocities have satisfied the focusing requirement (both |v r − v r | ≤ ρ r /T I and |v a −v a | ≤ ρ a /2T I are shown in Section 3.3.1), the amplitude of GRFT response is greater than the CFAR detection threshold. From [48], the CFAR detection threshold can be obtained as…”

Section: Procedures Of the Moving Ship Target Detection And Imagingmentioning

confidence: 99%

GRFT-Based Moving Ship Target Detection and Imaging in Geosynchronous SAR

et al. 2018

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Geosynchronous synthetic aperture radar (GEO SAR) has great potentials in ship surveillance due to its high time resolution and wide swath coverage. However, the remote slant range will result in a very low signal-to-noise ratio (SNR) of echoes that need to be enhanced by long-time coherent integration. The generalized Radon-Fourier transform (GRFT) can realize the coherent integration of moving target under long integration time by jointly parameter searching along range and velocity directions. Unfortunately, in GEO SAR, the very large slant range and long synthetic aperture will cause the curved synthetic aperture trajectory and non-negligible signal round-trip delay, leading to the failure of the traditional slant range and GRFT signal model for moving targets. This paper proposes an improved GRFT-based approach to realize the detection and imaging of moving ship targets in GEO SAR. Firstly, the accurate slant range for moving ship targets is constructed and the GRFT signal is redefined considering the curved trajectory and signal round-trip delay in GEO SAR. Then, GRFT responses to different motion parameters are analyzed. The procedures of moving ship targets detection and imaging in GEO SAR are presented through the detection with coarse-searched motion parameters in GRFT and the following imaging with fine-searched motion parameters based on minimum entropy. Finally, computer simulations verify the proposed GRFT-based method. be observed within the range of every 1.5-2.5 h per day [14]. Thus, GEO SAR has great advantages in ship surveillance over vast ocean area.Currently, there are growing interests for GEO SAR, which are mainly concentrated on system design and mission planning [15][16][17][18][19][20][21], imaging algorithms [22][23][24][25], ionospheric effects and compensation [26][27][28], and deformation retrieval [29][30][31]. However, there are rarely related researches on detection and imaging of moving ships.Obviously, due to high time resolution and wide swath coverage, GEO SAR has great potential in monitoring moving ships. However, the remote slant range of GEO SAR will result in a very low signal-to-noise ratio (SNR) of echoes. The defect of low SNR can be compensated for the static target through long time integration [32]. Unfortunately, the parameters of moving targets are unknown, leading to the failure of coherent integration and the resultantly SNR loss. Therefore, traditional detection and imaging methods for moving targets used in LEO SAR and airborne SAR are not suitable for GEO SAR.Moving targets detection and imaging can be divided into single-channel and multi-channel SAR schemes according to SAR system configuration. Because of the limitation of low SNR, multichannel configuration cannot be realized currently, as it is mainly designed for clutter suppression where ships have higher radar cross section (RCS) against the surrounding sea background (in general, ships has higher backscattering energy as the metallic materials and corner reflection structures [33,34]). Therefore, mo...

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