Adaptive modelling of sea clutter and detection of small targets in heavy clutter

Suvorova, Sofia; Moran, B.A.; Viola, M. L. Lanfredi

doi:10.1109/radar.2003.1278812

Cited by 12 publications

(4 citation statements)

References 8 publications

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“…The availability of short time-scale clutter measurements has been shown to dramatically improve detection probability [31] in dynamic clutter. We expect significant further improvements from instantaneous radar polarimetry.…”

Section: Discrimination In Cluttermentioning

confidence: 99%

A Simple Signal Processing Architecture for Instantaneous Radar Polarimetry

Howard

Calderbank

Moran

2007

IEEE Trans. Inform. Theory

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Abstract-This paper describes a new radar primitive that enables instantaneous radar polarimetry at essentially no increase in signal processing complexity. This primitive coordinates transmission of distinct waveforms on orthogonal polarizations and applies a unitary matched filter bank on receive. This avoids the information loss inherent in single-channel matched filters. A further advantage of this scheme is the elimination of range sidelobes.

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Section: Discrimination In Cluttermentioning

confidence: 99%

A Simple Signal Processing Architecture for Instantaneous Radar Polarimetry

Howard

Calderbank

Moran

2007

IEEE Trans. Inform. Theory

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“…One of the hot topics of research in radar, sonar, and communication engineering like cognitive radios is detection [ 10 , 11 ]. Detectors are the hub of radar systems and have extensively been addressed in the past [ 12 , 13 ]. The most commonly used detection method is cross-correlation.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Fusion Based Passive Multistatic Radar Detection

Asif

Kandeepan

2021

Sensors

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Passive multistatic radars have gained a lot of interest in recent years as they offer many benefits contrary to conventional radars. Here in this research, our aim is detection of target in a passive multistatic radar system. The system contains a single transmitter and multiple spatially distributed receivers comprised of both the surveillance and reference antennas. The system consists of two main parts: 1. Local receiver, and 2. Fusion center. Each local receiver detects the signal, processes it, and passes the information to the fusion center for final detection. To take the advantage of spatial diversity, we apply major fusion techniques consisting of hard fusion and soft fusion for the case of multistatic passive radars. Hard fusion techniques are analyzed for the case of different local radar detectors. In terms of soft fusion, a blind technique called equal gain soft fusion technique with random matrix theory-based local detector is analytically and theoretically analyzed under null hypothesis along with the calculation of detection threshold. Furthermore, six novel random matrix theory-based soft fusion techniques are proposed. All the techniques are blind in nature and hence do not require any knowledge of transmitted signal or channel information. Simulation results illustrate that proposed fusion techniques increase detection performance to a reasonable extent compared to other blind fusion techniques.

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“…Therefore, we present a subspace-based sea clutter suppression method in this paper. It maps the echo signal of sea clutter into low order subspace to suppress the clutter [6], and makes radar easily find the targets. Thus the detection performance is improved effectively.…”

Section: Introductionmentioning

confidence: 99%

A Sea Clutter Suppression Algorithm by Statistics Estimation and Subspace Analysis

Xue¹,

Mei²,

Liu³

2015

Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference

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Abstract.To solve the problem of target detection in heavy sea clutter, we make simulation study on a subspace-based clutter suppression method to improve signal to clutter ratio in the predicted target location, and thus to improve the detection performance. With the compound Gaussian model of the sea clutter, we first estimate the statistics of sea clutter by Expectation-Maximization (EM) algorithm, then exploit a subspace-based approach to further mitigate sea clutter. With the algorithm, the computational complexity is effectively reduced. Nonetheless the algorithm exhibits good performance of clutter suppression. Numerical results show that the algorithm is effective in sea clutter suppression. Fig.1 The structure of clutter suppression system.

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Adaptive modelling of sea clutter and detection of small targets in heavy clutter

Cited by 12 publications

References 8 publications

A Simple Signal Processing Architecture for Instantaneous Radar Polarimetry

A Simple Signal Processing Architecture for Instantaneous Radar Polarimetry

Cooperative Fusion Based Passive Multistatic Radar Detection

A Sea Clutter Suppression Algorithm by Statistics Estimation and Subspace Analysis

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