Fluctuating target detection in presence of non Gaussian clutter in OFDM radars

Kafshgari, Shaghayegh; Mohseni, Reza Moosavi

doi:10.1016/j.aeue.2013.04.014

Cited by 10 publications

(15 citation statements)

References 22 publications

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“…As the number of subcarrier increases, the dimension of measurement will grow rapidly and it would be difficult to compute. Hence we select a small number of subcarriers to evaluate our algorithm (in similar literatures, [10] sets N = 2, 4, 6 and [13] sets N = 1, 3, 5).…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The problem of target detection in multipath scenarios is reformulated as sparse spectrum estimation and the spectral parameters of OFDM radar waveform are optimized based on multi-objective optimization (MOO) technique to improve the detection performance [11]. The performances of generalized likelihood ratio test (GLRT) detector with OFDM radar in non-Gaussian clutter (including Log-normal, Weibull and K-compound distribution) were investigated in [12,13] and target fluctuations were also taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Target Detection in Compound-Gaussian Clutter With Adaptive Ofdm Radar

Xia¹,

Song²,

Lu³

et al. 2016

PIER M

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This paper mainly deals with the problem of target detection in compound-Gaussian clutter with orthogonal frequency division multiplexing (OFDM) radar. First, the OFDM measurement model is developed to compound-Gaussian clutter by taking advantage of frequency diversity of OFDM radar waveform and we devise a generalized likelihood rate test (GLRT) detector where the target scattering coefficients and clutter covariance matrix are unknown. Then, we propose an adaptive waveform design scheme based on maximizing Mahalanobis distance of the distributions under two hypothesises to improve the detection performance. Finally, the effectiveness of the proposed detector as well as the adaptive waveform design method is demonstrated via numerical examples.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Target Detection in Compound-Gaussian Clutter With Adaptive Ofdm Radar

Xia¹,

Song²,

Lu³

et al. 2016

PIER M

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show abstract

“…OFDM radar signals have several particular advantages [3][4][5], which are suitable for realization of the cognitive radar. There are two main reasons: 1) The design of OFDM signal is flexible, which is convenient for waveform adjustment of the cognitive radar.…”

Section: Introductionmentioning

confidence: 99%

An adaptive waveform design method for OFDM cognitive radar

Huang

Qiu

Liu

et al. 2014

2014 International Radar Conference

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With fixed emitted waveforms, traditional radars could not achieve optimal performance when the target and environment change. Cognitive radar can apperceive changing information outside, feed back to the transmitter intelligently, and then adjust waveforms to achieve better performance. Therefore, cognitive radar can fit the fast changing environment of modern battlefield better than the traditional radar. The advantage of OFDM signals for cognitive radar is analyzed in this paper firstly. And then, a new architecture of OFDM cognitive radar is proposed. The crucial component -adaptive waveform design for the OFDM cognitive radar is addressed to solve the key problem of "learning" and "feedback" in cognitive radar. The main idea is to establish the "estimationoptimization" mechanism to handle the changing of the target and the surrounding environment. Simulation results demonstrate that the performance of OFDM cognitive radar is better than that of traditional radar.

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“…It had been shown that multipath reflections affects categorized into two different aspects, namely, multipath suppression and multipath utilization. Some methods regard the multipath effect as a clutter component and try to suppress it [4][5][6][7][8][9][10][11][12]. Numerous methods, such as spatial smoothing techniques, proposed removing the coherency [13,14].…”

Section: Introductionmentioning

confidence: 99%

An edge computing framework based on OFDM radar for low grazing angle target tracking

Karimi

Mohseni

Khosravi

2020

J Wireless Com Network

Self Cite

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In this paper, a novel adaptive algorithm to detect and track targets with low grazing angle is addressed. For this purpose, an orthogonal frequency division multiplexing (OFDM) radar signal is employed through an edge computing framework over the radar platform. However, detecting the targets in the low grazing angle area is a great challenge due to severe multipath reflection effects. The Earth's curvature geometry model is presented as the multipath propagation model. Based on the fact that the different scattering centers of a target resonate at different frequencies, we use the optimized OFDM waveform and propose a novel target tracking procedure for low grazing angle target tracking scenarios. The obtained results show that using an OFDM radar waveform provides a more uniform detection coverage in the presence of multipath propagation such that this will fill in the nulls. Finally, simulations are used to compare the performance of the proposed OFDM waveform with the conventional equal-power, the generalized likelihood ratio (GLR)-based and single-carrier waveforms.

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Fluctuating target detection in presence of non Gaussian clutter in OFDM radars

Cited by 10 publications

References 22 publications

Target Detection in Compound-Gaussian Clutter With Adaptive Ofdm Radar

Target Detection in Compound-Gaussian Clutter With Adaptive Ofdm Radar

An adaptive waveform design method for OFDM cognitive radar

An edge computing framework based on OFDM radar for low grazing angle target tracking

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