A State Identification Method for 1-D Measurements with Gaps

Piou, Jean E.

doi:10.2514/6.2005-5943

Cited by 35 publications

(49 citation statements)

References 3 publications

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“…The number of these terms equals the number of the scattering points in the view of the antenna and multiple scattering effect [6]. In fact, the frequency response could be represented in the following form [7],…”

Section: Frequency Domain Mathematical Model Of the Signalmentioning

confidence: 99%

See 1 more Smart Citation

Frequency Domain Skin Artifact Removal Method for Ultra-Wideband Breast Cancer Detection

Maskooki¹,

Soh²,

Gunawan³

et al. 2009

PIER

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Abstract-Using ultra-wide band (UWB) microwave pulse for breast cancer detection has been greatly investigated recently since it does not expose the patient to any harmful radiation and the implementation is relatively cheaper than other methods such as MRI or X-ray. An issue in UWB imaging of breast cancer is the strong backscatter from the breast skin which is in orders of magnitude larger than the pulse backscattered from the tumor and should be eliminated before processing the signal for the tumor detection and imaging. At present no existing method can effectively remove this artifact without introducing corruption to the tumor signature. In this paper, a novel method to eliminate this artifact is proposed which employs a frequency domain model to isolate and remove skin related information from the signal. This method is compared with the existing methods of the skin artifact removal in different scenarios. The results show that the new method can overcome the shortcomings of the previous methods and improve the detection of the tumor in the sense of the tumor to clutter response ratio.

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Section: Frequency Domain Mathematical Model Of the Signalmentioning

confidence: 99%

“…Now, we will provide the formulation to estimate model parameters in (2) which is described in detail by Piou in [7]. From the system theory we know that the following state-space equations hold for inputoutput relation in a linear system.…”

Section: State -Space Representation Of the Signalmentioning

confidence: 99%

Frequency Domain Skin Artifact Removal Method for Ultra-Wideband Breast Cancer Detection

Maskooki¹,

Soh²,

Gunawan³

et al. 2009

PIER

View full text Add to dashboard Cite

show abstract

“…The received signals are first converted to the frequency domain using the Fast Fourier Transform (FFT) algorithm. These frequency domain signals are then processed using the linear system identification method to estimate the frequency model given in (21) [15]. The frequency domain signal is arranged in the form of a Hankel matrix as follows:…”

Section: Frequency Domain Pole Splittingmentioning

confidence: 99%

Artifact Removal Algorithms for Microwave Imaging of the Breast

Elahi¹,

Glavin²,

Jones³

et al. 2013

PIER

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Abstract-One of the most promising alternative imaging modalities for breast cancer detection involved the use of microwave radar systems. A critical component of any radar-based imaging system for breast cancer detection is the early-stage artifact removal algorithm. Many existing artifact removal algorithms are based on simplifying assumptions about the degree of commonality in the artifact across all channels. However, several real-world clinical scenarios could result in greater variation in the early-stage artifact, making the artifact removal process much more difficult. In this study, a range of existing artifact removal algorithms, coupled with algorithms adapted from Ground Penetrating Radar applications, are compared across a range of appropriate performance metrics.

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“…Reference [1] uses the all-pole model and the root-MUSIC for model parameter estimation. In [12,13], an 1-D gapped-data state space approach (1-D GSSA) is used to estimate parameters of complex exponential (CE) model for gaps data estimation. In [14,15], the Lpnorm regularization method with 0 < p < 1 is applied for partialaperture and sparse band imaging, where the choice of p remains an open problem.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], a data based coherent compensation method is used for coherent processing, but it is easily influenced by noise due to lack of de-noising process. For the data fusion methods, the available algorithms include nonparametric spectrum estimation [6][7][8][9][10], the parametric spectrum estimation method [1,12,13] and p-norm regularization method [14]. In [6], Burg algorithm is used to find the linear prediction parameters and a iterative procedure is used to improve the estimation of the parameters and the extrapolation of the data, but the gaps between subbands can not be too large.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Imaging Based on Coherent Processing for Distributed Multi-Band Radar Data

He¹,

Xu²

2013

PIER

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Abstract-A coherent processing method for subband signals of distributed multi-band radar data is proposed and tested. The method uses de-noising cross-correlation (DNCC) algorithm and statistical method to obtain phase incoherent parameters (ICP) between subband signals. After compensating the phase ICP, a coherence function is defined and combined with statistical method to find amplitude ICP. Finally, data fusion method via two-dimensional gapped-data state space approach (2-D GSSA) is applied to subband signals and high-resolution imaging of target is achieved. The advantage of this method lies in that it can be used to process subband signals of different bandwidth and different gaps between them. To validate our work, electromagnetic calculation target and real target measured in microwave chamber are analyzed and used for testing different mutual-coherence and data fusion algorithms. Experimental results demonstrate the superiority of the proposed method over previous approaches in terms of improved imaging quality and performance.

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A State Identification Method for 1-D Measurements with Gaps

Cited by 35 publications

References 3 publications

Frequency Domain Skin Artifact Removal Method for Ultra-Wideband Breast Cancer Detection

Frequency Domain Skin Artifact Removal Method for Ultra-Wideband Breast Cancer Detection

Artifact Removal Algorithms for Microwave Imaging of the Breast

High-Resolution Imaging Based on Coherent Processing for Distributed Multi-Band Radar Data

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