• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.619-627
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• 2017

MIMO(Multi-Input Multi-Output) radar is an emerging radar technology for its numerous advantages. However, in the electric warfare viewpoint, MIMO radar is a new developed radar technology for that existing parameter estimation cannot applied and a new radar parameter estimation based on the characteristics of MIMO radar is desired. In this paper, we propose a blind estimation scheme for the number of orthogonal waveforms of a uniform linear array(ULA) MIMO radar using minimum two electronic sensors.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.80-86
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• 2010

Compressive Sensing (CS) has been widely studied as a promising technique in many applications. The CS theory tells that a signal that is known to be sparse in a specific basis can be reconstructed using convex optimization from far fewer samples than traditional methods use. In this paper, we apply CS technique to Multiple-input multiple-output (MIMO) radar systems which employ uniform linear arrays (ULA). Especially, we investigate the problem of finding the direction-of-arrival (DOA) using CS technique and compare the performance with the conventional adaptive MIMO techniques. The results suggest the CS method can provide the similar performance with far fewer snapshots than the conventional adaptive techniques.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.891-897
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• 2018

In this paper, we propose a blind estimation scheme for the antenna spacing of nonuniform linear array MIMO radar using distributed electronic sensors based on ESPRIT. We present a blind method to separate orthogonal waveforms of a MIMO radar based on the antenna spacing estimation. The estimated orthogonal waveforms of a MIMO radar can be used for disabling opponent MIMO radars.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.204-210
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• 2012

In this paper, we study the method of estimating direction of departure(DOD) and direction of arrival(DOA) using estimation of signal parameters via rotational invariant techniques (ESPRIT) in uniform linear array MIMO radar system. While it is possible to improve the resolution by increasing the numbers of physical antennas and snapshots after matched filtering, such methods generally give rise to increase in complexity. In this paper, we propose to improve the resolution by optimally allocating the number of transmit and receive antennas. In particular, we show that the performance is optimized when the number of the receive antennas is approximately twice that of transmit antennas.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.782-790
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• 2014

In this paper, we apply the 2-D Matrix Pencil Method(MPM) to the estimation of the direction of arrival(DOA) of multiple signals of interest(SOIs) in bistatic MIMO radar. The 2-D MPM shows remarkable performance under a low SNR environment and low computational complexity to estimate the DOA of multiple SOIs. Also, it is possible to estimate the direction of departure(DOD) which is an angle from transmitter to target. To verify the proposed algorithm, we applied the proposed algorithm to a uniformly spaced linear array(ULA) and compared the RMSE(Root Mean Square Error) of DOA and DOD under the various SNR with those of the 2-D Capon algorithm.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.952-959
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• 2012

In this paper, we propose an ESPRIT based algorithm for target position estimation with uniform linear array (ULA) and uniform circular array (UCA) at transmitter and receiver, respectively. When UCA is adopted at the receiver, unlike the case of ULA at the receiver, the rotational invariance of the received signal is satisfied. Although there has been an attempt to resolve this issue, the problem of direction of departure estimation has not been considered. In this paper, we provide an ESPRIT based algorithm to simultaneously estimate transmitter elevation angle, receiver elevation angle, and receiver azimuth angle, taking into account the transmitter antennas as well as the receiver antennas.