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| 2. |
- Gianelli, Christopher, et al.
(författare)
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One-Bit Compressive Sampling with Time-Varying Thresholds : Maximum Likelihood and the Cramer-Rao Bound
- 2016
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Ingår i: 2016, 50Th Asilomar Conference On Signals, Systems And Computers. - : IEEE COMPUTER SOC. - 9781538639542 ; , s. 399-403
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Konferensbidrag (refereegranskat)abstract
- This paper considers the problem of estimating the parameters of a noisy signal which has been quantized to one-bit via a time-varying thresholding operation. An expression for the Fisher information matrix (FIM) is derived for a generic deterministic signal parameterized by a vector beta when the noise is independent and identically distributed (i.i.d.) Gaussian with either known or unknown variance. The case of single sinusoidal parameter estimation is considered as a particular example, and the Cramer-Rao bounds (CRB) for amplitude, frequency, and phase estimators are computed for a variety of parameter values. A maximum likelihood (ML) estimator for the sinusoidal signal parameters is proposed, and its performance is compared with the CRB as a function of the number of observations.
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| 3. |
- Gianelli, Christopher, et al.
(författare)
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One-bit Compressive Sampling with Time-Varying Thresholds for Multiple Sinusoids
- 2017
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Ingår i: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). - : IEEE. - 9781538612514
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Konferensbidrag (refereegranskat)abstract
- Wide-band spectral sensing is a challenging task that will be required in future cognitive radio and radar applications. Recent research has shown that sampling using only one-bit of amplitude precision can be realized at an extremely high rate [1] in an affordable manner. In this work, one-bit sampling using time-varying thresholds is considered for line spectral estimation. The time-varying thresholds allow for amplitude estimation. A novel one-bit RELAX algorithm is developed for multi-tone parameter estimation. This algorithm is shown to have excellent performance via a numerical example.
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| 5. |
- Karlsson, Johan, et al.
(författare)
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Fast Missing-Data IAA With Application to Notched Spectrum SAR
- 2014
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Ingår i: IEEE Transactions on Aerospace and Electronic Systems. - 0018-9251 .- 1557-9603. ; 50:2, s. 959-971
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Tidskriftsartikel (refereegranskat)abstract
- Recently, the spectral estimation method known as the iterative adaptive approach (IAA) has been shown to provide higher resolution and lower sidelobes than comparable spectral estimation methods. The computational complexity is higher than methods such as the periodogram (matched filter method). Fast algorithms have been developed that considerably reduce the computational complexity of IAA by using Toeplitz and Vandermonde structures. For the missing-data case, several of these structures are lost, and existing fast algorithms are only efficient when the number of available samples is small. In this work, we consider the case in which the number of missing samples is small. This allows us to use low-rank completion to transform the problem to the structured problem. We compare the computational speed of the algorithm with the state of the art and demonstrate the utility in a frequency-notched synthetic aperture radar imaging problem.
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| 6. |
- Li, Jian, et al.
(författare)
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On Parameter Identifiability of MIMO Radar
- 2007
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Ingår i: IEEE Signal Processing Letters. - 1070-9908 .- 1558-2361. ; 14:12, s. 968-971
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Tidskriftsartikel (refereegranskat)abstract
- A multi-input multi-output (MIMO) radar system, unlike a standard phased-array radar, can transmit multiple linearly independent probing signals via its antennas. We show herein that this waveform diversity enables the MIMO radar to significantly improve its parameter identifiability. Specifically, we show that the maximum number of targets that can be uniquely identified by the MIMO radar is up to Mt times that of its phased-array counterpart, where Mt is the number of transmit antennas.
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| 7. |
- Li, Jian, et al.
(författare)
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Range compression and waveform optimization for MIMO radar : a Cramér-Rao bound based study
- 2008
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Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 56:1, s. 218-232
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Tidskriftsartikel (refereegranskat)abstract
- A multi-input multi-output (MIMO) radar system, unlike standard phased-array radar, can transmit via its antennas multiple probing signals that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar enables superior capabilities compared with a standard phased-array radar. One of the common practices in radar has been range compression. We first address the question of "to compress or not to compress" by considering both the Cramer-Rao bound (CRB) and the sufficient statistic for parameter estimation. Next, we consider MIMO radar waveform optimization for parameter estimation for the general case of multiple targets in the presence of spatially colored interference and noise. We optimize the probing signal vector of a MIMO radar system by considering several design criteria, including minimizing the trace, determinant, and the largest eigenvalue of the CRB matrix. We also consider waveform optimization by minimizing the CRB of one of the target angles only or one of the target amplitudes only. Numerical examples are provided to demonstrate the effectiveness of the approaches we consider herein.
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| 11. |
- Stoica, Peter, et al.
(författare)
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Adaptive beamforming for quadrupole resonance
- 2007
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Ingår i: Digital signal processing (Print). - : Elsevier BV. - 1051-2004 .- 1095-4333. ; 17:3, s. 634-651
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Tidskriftsartikel (refereegranskat)abstract
- We present several adaptive beamforming approaches to improve the quadrupole resonance (QR) signal detection performance via exploiting both the spatial and temporal correlation of radio frequency interferences (RFIs). We operate in the framework of signal amplitude estimation with known signal waveform and make use of three adaptive beamforming approaches, viz., the standard Capon beamformer (SCB), the robust Capon beamformer (RCB), and the amplitude and phase estimation (APES) algorithm, to develop several new approaches for mitigating the spatially and temporally correlated RFIs. Simulated and experimental results are provided to demonstrate the effectiveness of the proposed approaches.
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| 12. |
- Stoica, Peter, et al.
(författare)
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Optimal correction of an indefinite estimated MA spectral density matrix
- 2007
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Ingår i: Statistics and Probability Letters. - : Elsevier BV. - 0167-7152 .- 1879-2103. ; 77:10, s. 973-980
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Tidskriftsartikel (refereegranskat)abstract
- Consider a vector moving-average sequence of order n, MA (n), and let Φ (ω) = ∑k = - nn Rk e- j ω k denote its spectral density matrix, where { Rk }k = - nn are the covariance matrices and ω stands for the frequency variable. A nonparametric estimate over(Φ, ^) (ω) = ∑k = - nn over(R, ^)k e- j ω k of Φ (ω) can easily become indefinite at some frequencies, and thus invalid, due to the estimation errors. In this paper, we provide a computationally efficient procedure that obtains the optimal (in a least-squares sense) valid approximation Φ (ω) to over(Φ, ^) (ω) in a polynomial time, by means of a semidefinite programming (SDP) algorithm.
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| 13. |
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| 14. |
- Xie, Yao, et al.
(författare)
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Multistatic adaptive microwave imaging for early breast cancer detection
- 2006
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 53:8, s. 1647-1657
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Tidskriftsartikel (refereegranskat)abstract
- We propose a new multistatic adaptive microwave imaging (MAMI) method for early breast cancer detection. MAMI is a two-stage robust Capon beamforming (RCB) based image formation algorithm. MAMI exhibits higher resolution, lower sidelobes, and better noise and interference rejection capabilities than the existing approaches. The effectiveness of using MAMI for breast cancer detection is demonstrated via a simulated 3-D breast model and several numerical examples.
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| 15. |
- Xu, Luzhou, et al.
(författare)
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A block-diagonal growth curve model
- 2006
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Ingår i: Digital signal processing (Print). - : Elsevier BV. - 1051-2004 .- 1095-4333. ; 16:6, s. 902-912
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Tidskriftsartikel (refereegranskat)abstract
- We consider a variation of the growth curve (GC) model, referred to as the block-diagonal growth curve (BDGC) model, where the unknown regression coefficient matrix is constrained to be block-diagonal. A closed-form approximate maximum likelihood (AML) estimator for this model is derived based on the maximum likelihood principle. We analyze the statistical properties of this method theoretically and show that the AML estimate is unbiased and asymptotically statistically efficient for a large snapshot number. Via numerical examples in wireless communications, we also show that the proposed AML estimator can achieve excellent estimation accuracy.
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| 16. |
- Xu, Luzhou, et al.
(författare)
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A diagonal growth curve model and some signal processing applications
- 2006
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Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 54:9, s. 3363-3371
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Tidskriftsartikel (refereegranskat)abstract
- We consider a variation of the growth-curve (GC) model, referred to as the diagonal growth-curve (DGC) model, where the steering vectors and waveforms are both known and the complex amplitude matrix is constrained to be diagonal. A closed-form approximate maximum likelihood (AML) estimator for this model is derived based on the maximum likelihood principle. We analyze the statistical properties of this method theoretically and show that the AML estimate is unbiased and asymptotically statistically efficient for a large snapshot number. Via several numerical examples in array signal processing and spectral analysis, we also show that the proposed AML estimator can achieve better estimation accuracy and exhibit greater robustness than the best existing methods.
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| 17. |
- Xu, Luzhou, et al.
(författare)
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Adaptive techniques for MIMO radar
- 2006
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Ingår i: Proceedings of the 4th IEEE Workshop on Sensor Array and Multi-Channel Processing (SAM 2006).
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Konferensbidrag (refereegranskat)
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| 22. |
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| 23. |
- Xu, Luzhou, et al.
(författare)
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Wideband source localization using sparse learning via iterative minimization
- 2013
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 93:12 SI, s. 3504-3514
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, two extensions of the Sparse Learning via Iterative Minimization (SLIM) algorithm are presented for wideband source localization using a sensor array. The proposed methods exploit the joint sparse structure across all frequency bins, and estimate the spatial pseudo-spectra at various frequency bins jointly and iteratively. Via several numerical examples, we show that the proposed methods can provide high-resolution angle estimates and excellent sourcelocalization performance, and are able to resolve the left-right ambiguity problem, when used together with the vector sensor array technology.
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| 24. |
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