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We investigate the algorithm of direction and Doppler frequency estimation for bistatic multiple-input multiple-output (MIMO) radar in spatial colored noise. A novel method of joint estimation of direction and Doppler frequency in spatial colored noise based on propagator method (PM) for bistatic MIMO radar is discussed. Utilizing the cross-correlation matrix which is formed by the adjacent outputs of match filter in the time domain, the special matrix is constructed to eliminate the influence of spatial colored noise. The proposed algorithm provides lower computational complexity and has very close parameters estimation compared to estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm in high signal-to-noise ratio (SNR). It is applicable even if the transmitted waveforms are not orthogonal. The estimated parameters can be paired automatically and the Cramér-Rao Bound (CRB) is given in spatial colored noise. Simulation results confirm the effectiveness of the proposed method.

Since multiple-input multiple-output (MIMO) radars use multiple antennas to simultaneously transmit diverse waveforms and utilize multiple antennas to receive the reflected signals, they have many potential advantages over conventional phased-array radars [

Target direction estimation is a basic function of a radar system. Many advanced direction estimation algorithms for MIMO radar have been extensively discussed in the current literature which include ESPRIT algorithm, Capon algorithm, parallel factor (PARAFAC) algorithm, multiple signal classification (MUSIC) algorithm, and PM algorithm [

The remainder of this paper is structured as follows. Section

We consider a narrowband bistatic MIMO radar system with

The covariance matrix of

We assume that

Note that

The covariance matrix of

We define

We also define

Now we show the major steps of the proposed algorithm as follows.

Compute the covariance matrix of the received data through (

Estimate the propagator

Compute the Doppler frequency according to (

Estimate matrix

In fact completely orthogonal signals cannot be found in reality, if we consider the transmitted nonorthogonal signals; that is,

In contrast to ESPRIT algorithm [

Complexity comparison with

From Figure

Since the DOA-DODs and Doppler frequencies are given through the corresponding eigenvectors, it can achieve automatically paired estimation of angles and Doppler frequencies.

The proposed algorithm can eliminate the effect of the spatial colored noise since the new matrix is constructed by (

In this section, we derive CRB of parameter estimation for MIMO radar and rewrite the received data as

We present the Monte Carlo simulations to assess the parameter estimation performance of our algorithm. Define root mean squared error (RMSE) as

Angle and Doppler frequency estimation at SNR = 10 dB.

Figures

Angle estimation comparison performance.

Doppler frequency estimation comparison.

The simulation of Figures

Angle estimation with different values of

Doppler frequency estimation with different values of

Figure

Angle and Doppler frequency estimation at SNR = 12 dB.

We have presented a low-complexity angle and Doppler frequency estimation based on propagator method for MIMO radar in spatial colored noise. The proposed algorithm can obtain automatically paired transmit and receive angle estimations in the MIMO radar and eliminate the influence of the spatial colored noise. Furthermore, it provides lower computational complexity and has close parameters estimation compared to ESPRIT algorithm and DOA matrix algorithm in high SNR. It is applicable even if the transmitted waveforms are not orthogonal.

The authors declare that there is no conflict of interests regarding the publication of this paper.

This work is supported by Nanjing University of Aeronautics and Astronautics Research Funding (NZ2013208). The authors are grateful to the anonymous referees for their constructive comments and suggestions in improving the quality of this paper.