Direction-of-arrival estimation of nonstationary signals exploiting signal characteristics

Zhang, Yimin D.; Amin, Moeness G.; Himed, Braham

doi:10.1109/isspa.2012.6310479

Cited by 20 publications

(7 citation statements)

References 17 publications

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“…We can design a narrowband filter to keep the ith component and to filter out the other multipath components. Note that unlike in the directionof-arrival estimation approaches [14] where only a single zero-frequency bin is used, we need to capture multiple frequency bins of the stationarized ith component so as to keep the time-varying Doppler information, which is particularly important to determine the direction of the elevation velocity of the target. The captured signal vector is multiplied by exp(jψ i,k ) to restore the original Doppler information in each signal component., i.e.,…”

Section: Signal Filteringmentioning

confidence: 99%

Instantaneous altitude estimation of maneuvering target in over-the-horizon radar exploiting multipath Doppler signatures

Zhang

Amin

et al. 2013

EURASIP J. Adv. Signal Process.

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Over-the-horizon radar systems are capable of localizing targets in range and azimuth but are unable to achieve reliable altitude estimation. Past work has shown that the time-varying Doppler signatures of micro-multipath signals provide rich information for reliable estimation of altitude changes. In this paper, we develop a new technique for the estimation of instantaneous altitude of maneuvering targets by exploiting the estimated multicomponent Doppler signatures. A key contribution of this paper is to apply effective non-stationary signal analysis techniques for estimating the time-varying Doppler signature of each individual multipath. This enables reliable target altitude estimation in an extended Kalman filter setup. The maximum a-posteriori criterion is used for the estimation of initial target states.

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Section: Signal Filteringmentioning

confidence: 99%

Instantaneous altitude estimation of maneuvering target in over-the-horizon radar exploiting multipath Doppler signatures

Zhang

Amin

et al. 2013

EURASIP J. Adv. Signal Process.

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“…This can be done by resorting to the time-frequency (TF) analysis, which is a powerful tool for nonstationary signal representation [11]. By turning to the TF analysis framework, we are able to exploit the inherent time-frequency-space characteristics of the underlying array signal to achieve better performance even in a noisy and coherent environment with few snapshots [12]. The definition of spatial time-frequency distribution (STFD) was first introduced by Belouchrani and Amin in [11], where the diagonalization of a combined set of STFD matrices was used to solve the problem of blind source separation for non-stationary signals.…”

Section: Introductionmentioning

confidence: 99%

Vector-sensor array direction-of-arrival estimation exploiting spatial time-frequency structure based on joint approximate diagonalization

Song

Yang

Wang

2019

Acoust. Sci. & Tech.

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By making use of the extra particle velocity information, an array of vector sensors can achieve better Direction-of-arrival (DOA) estimation performance than a conventional array of pressure sensors. However, it is noted that most of the previous work on DOA estimation with vectorsensor array uses only the time-space statistical information available on the array signals and does not exploit the difference in the time-frequency signatures of the sources. In this paper, we develop a new approach which exploits the inherent time-frequency-space characteristics of the underlying vectorsensor array signal to achieve better DOA estimation performance even in a noisy and coherent environment with few snapshots. It turns out that our approach is based on the spatial time-frequency distributions (STFD) information and can efficiently combine all of the relevant STFD points by the joint approximate diagonalization approach, such as Jacobi rotation, to reduce the effect of noise and achieve the desired angular resolution. Computer simulations with several frequently encountered scenarios, such as multiple closely spaced coherent sources, indicate the superior DOA estimation resolution of our proposed approach as compared with existing techniques. In addition, from a statistical point of view, the performance of our proposed approach is investigated more closely by considering the root mean square error (RMSE) respectively versus SNRs, snapshots, or number of sensors and its excellent performance for higher DOA estimation accuracy is demonstrated.

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“…Under this scenario, auto-terms t-f points [18], [20], [25], [27], [30] or cross-terms t-f points [19] have been considered to construct STFD matrices. Due to the computational complexity and the cross-terms of quadratic t-f analysis tools, the linear t-f analysis tools, e.g., the fractional Fourier transform (FRFT) [10], [13], [15], [16], [32] and the short-time Fourier transform (STFT) [33][34][35], also have been applied to the DOA estimation field. These algorithms also use the above two assumptions, which means they all cannot resolve the t-f completely or largely joint sources (the t-f points of the sources are all the same or the sources have a lot of the same t-f points), which limits their further developments.…”

Section: Introductionmentioning

confidence: 99%

DOA Estimation of Multiple LFM Sources Using a STFT-based and FBSS-based MUSIC Algorithm

Cui¹,

Chen²,

Huang³

et al. 2017

RADIOENGINEERING

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Abstract. Direction of arrival (DOA) estimation is an important problem in array signal processing. An effective multiple signal classification (MUSIC) method based on the short-time Fourier transform (STFT) and forward/ backward spatial smoothing (FBSS) techniques for the DOA estimation problem of multiple time-frequency (t-f) joint LFM sources is addressed. Previous work in the area e. g. STFT-MUSIC algorithm cannot resolve the t-f completely or largely joint sources because they can only select the single-source t-f points. The proposed method constructs the spatial t-f distributions (STFDs) by selecting the multiple-source t-f points and uses the FBSS techniques to solve the problem of rank loss. In this way, the STFT-FBSS-MUSIC algorithm can resolve the t-f largely joint or

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Direction-of-arrival estimation of nonstationary signals exploiting signal characteristics

Cited by 20 publications

References 17 publications

Instantaneous altitude estimation of maneuvering target in over-the-horizon radar exploiting multipath Doppler signatures

Instantaneous altitude estimation of maneuvering target in over-the-horizon radar exploiting multipath Doppler signatures

Vector-sensor array direction-of-arrival estimation exploiting spatial time-frequency structure based on joint approximate diagonalization

DOA Estimation of Multiple LFM Sources Using a STFT-based and FBSS-based MUSIC Algorithm

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