Parameter estimation and identifiability in bistatic multiple-input multiple-output radar

Chan, Frankie K. W.; So, Hing Cheung; Huang, Longting

doi:10.1109/taes.2015.130502

Cited by 39 publications

(9 citation statements)

References 21 publications

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“…Recently, multiple-input/multiple-output (MIMO) systems attracted more and more attention [1,2,3]. There is rapidly growing literature concerning target parameter estimation in MIMO radar systems.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment

Younan

Shi

2019

Sensors

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Since second-order statistics-based methods rely heavily on Gaussianity assumption and fractional lower-order statistics-based methods depend on a priori knowledge of non-Gaussian noise, there remains a void in wideband bistatic multiple-input/multiple-output (MIMO) radar systems under impulsive noise. In this paper, a novel method based on Sigmoid transform was used to estimate target parameters, which do not need a priori knowledge of the noise in an impulsive noise environment. Firstly, a novel wideband ambiguity function, termed Sigmoid wideband ambiguity function (Sigmoid-WBAF), is proposed to estimate the Doppler stretch and time delay by searching the peak of the Sigmoid-WBAF. A novel Sigmoid correlation function is proposed. Furthermore, a new MUSIC algorithm based on the Sigmoid correlation function (Sigmoid-MUSIC) is proposed to estimate the direction-of-departure (DOD) and direction-of-arrival (DOA). Then, the boundness of the Sigmoid-WBAF to the symmetric alpha stable (SαS) noise, the feasibility analysis of the Sigmoid-WBAF, and complexity analysis of the Sigmoid-WBAF and Sigmoid-MUSIC are presented to evaluate the performance of the proposed method. In addition, the Cramér–Rao bound for parameter estimation was derived and computed in closed form, which shows that better performance was achieved. Simulation results and theoretical analyses are presented to verify the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment

Younan

Shi

2019

Sensors

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“…Mulitple-input multiple-output (MIMO) radar is an new emerging radar system that has been paid much attention recently. Compared with canonical phased-array radar, MIMO radar can transmit and receive independent waveforms via multiple antennas [1] and show advantage in resolution and better parameter identifiability [2].Recently, research on MIMO radar is mainly focused on waveform design, array configurations, imaging application, parameter estimation and otherwise [3]. In this paper, we focus on the colocated MIMO radar imaging issue.…”

Section: Introductionmentioning

confidence: 99%

Tensor-based Match Pursuit Algorithm for MIMO Radar Imaging

Huang¹,

Li²,

Wang³

2018

RADIOENGINEERING

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In MIMO radar, existing sparse imaging algorithms commonly vectorize the receiving data, which will destroy the multi-dimension structure of signal and cause the algorithm performance decline. In this paper, the sparsity characteristic and multi-dimension characteristic of signals are considered simultaneously and a new compressive sensing imaging algorithm named tensor-based match pursuit (TMP) is proposed. Firstly, MIMO radar tensor signal model is established to eliminate "dimension disaster". Then, exploiting tensor decomposition to process tensor data sets, tensor-based match pursuit is formulated for multi-dimension sparse signal recovery. Simulation results validates that the proposed method can accomplish high-resolution imaging correctly compared with conventional greedy sparse recovery algorithms. Additionally, under fewer snapshots condition, RMSE of proposed method is lower than other sparse recovery algorithms.

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“…MIMO radar is illustrated with an array of multiple sensors at both the transmitter and receiver. Based on the position of transmitting and receiving arrays, MIMO radars can be categorised into monostatic MIMO radar [3][4][5][6][7] and bistatic MIMO radar [8][9][10][11][12][13][14][15][16]. In the former, the arrays are closely spaced and in the later, arrays are spaced widely enough such that the direction of departure (DOD) and direction of arrival (DOA) are distinct.…”

Section: Introductionmentioning

confidence: 99%

“…The direction estimation in MIMO radar has been investigated by many researchers (see, e.g. [3][4][5][6][7][8][9][10][11][12][13][14][15][16]). Many of these investigations are focused on, either individually or jointly, the multiple signal classification (MUSIC) method and the estimation of signal parameters via rotational invariance technique (ESPRIT), and proven to be effective for uncorrelated signals.…”

Section: Introductionmentioning

confidence: 99%

Integrated polarisation and diversity smoothing algorithm for DOD and DOA estimation of coherent targets

Chintagunta

Palanisamy

2018

IET signal process.

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This study proposes a novel integrated polarisation and diversity smoothing (IPDS) algorithm to solve the direction estimation problem of coherent targets in bistatic multiple-input multiple-output (MIMO) radar with electromagnetic vector sensors (EVSs). The IPDS algorithm partitions the transmit and receive arrays into multiple subarrays based on the sensor elements and the spatial phase shift factors. Then the covariance matrices of the received signals from coherent targets associated with these subarrays are smoothened to restore the rank inadequacy of the reflection coefficient covariance matrix. After applying the IPDS algorithm, the direction of departure (DOD) and the direction of arrival (DOA) are estimated using the estimation of signal parameters via rotational invariance technique and the multiple signal classification methods. The effectiveness of the proposed algorithm in terms of decorrelation factor, estimation accuracy, precision and the spatial spectrum is evaluated through computer simulations. Cramér-Rao lower bound is derived for the bistatic MIMO radar with EVSs to substantiate the proposed algorithm. The simulation results are compared with the diversity smoothing and the polarisation smoothing algorithms available in literature. The results obtained by using the proposed algorithm were found to be impressive.

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Parameter estimation and identifiability in bistatic multiple-input multiple-output radar

Cited by 39 publications

References 21 publications

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment

Tensor-based Match Pursuit Algorithm for MIMO Radar Imaging

Integrated polarisation and diversity smoothing algorithm for DOD and DOA estimation of coherent targets

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