^{1}

^{1}

^{1}

The estimation of target parameters in MIMO radar signal processing is one of the most important research topics. An efficient implementation of the Maximum Likelihood estimator is presented in this paper to estimate the DOA (Direction of Arrival), initial velocity and acceleration of a maneuvering target in colocated MIMO radar. The target’s DOA is estimated in the first place, then a Maximum-Likelihood (ML) estimation based on peak search is applied to a two-dimensional grids providing estimation of initial velocity and acceleration. Simulations show that the MIMO radar has a better performance in DOA estimation than the phased array radar. By means of Monte Carlo simulations, the estimation error of initial velocity and acceleration on different SNRs are calculated. The results also suggest the effectiveness of this method.

The Multiple-Input Multiple-Output (MIMO) Radio Transmission Technology, has the potential to enhance system capacity and improve spectral efficiency without requiring extra emission signal bandwidth or transmission power [

MIMO radar employs multiple elements at both transmitting and receiving antennas as the phased array radar does, on flip side, MIMO radar transmits orthogonal or partially correlated waveforms. According to the antenna conﬁgura- tion, MIMO radar systems can be classified into two categories: collocated (coherent) MIMO radars are those with closely spaced antennas [

This paper considers parameters estimation of maneuvering target in colocated MIMO radar by developing a maximum-likelihood estimator. The MUltiple SIgnal Classification (MUSIC) is applied in the first place to estimate DOA, followed by a two-dimensional search applied to estimate the velocity and acceleration. Performance of estimation for phased array radar and MIMO radar are compared under the same condition. The root mean square errors (RMSE) of the ML estimation of target parameters are obtained by Monte Carlo simulations. Numerical results demonstrate that MIMO radar has better angle estimation performance compared with conventional phased array radar and verify the effectiveness of this method as well.

Let’s consider a MIMO radar system in which there are

and the receive steering vector is

Assuming that the target has a reflection coefficient

where

The total

where

Let

The probability density function of

where

where

The first term

It can be easily shown that the product in (9) yields a diagonal matrix with diagonal elements maintain a constant which equals to

In order to find the maximum likelihood estimations of the unknown parameters, it is necessary to perform a three-dimensional (3-D) search in the parameter space. From a practical point of view, such a 3-D search, for all possible values of DOA, velocity and acceleration of a target, can cause tremendous computational burden. Therefore, we propose a two-stage sequential estimation process.

As we simplify the target moving scenario by assuming the target is moving along a certain direction, a classical sub-space method, multiple signal classification, is used to estimate the DOA of the target which can be treated as static or relatively static. Then the estimation of initial velocity and acceleration can be obtained when the cost function in (10) achieves its maximum.

We consider a MIMO radar with 6 antennas both on transmitting and receiving ends. Antennas are uniformly spaced with an distance of

Monte Carlo simulations with 200 trials per signal-to-noise ratio (SNR) were conducted to acquire the RMSE of the ML estimation. The RMSE of DOA is shown in

This paper studies the performance of parameters estimation of maneuvering target in coherent MIMO radars with the application of maximum likelihood estimation. Numerical simulation results show that MIMO radar has a better angular resolution than conventional phased array radar. The effectiveness of maximum likelihood estimator is also verified through the simulations.

This work is supported by National Nature Science Foundation of China (NSFC)

under Grants 61471365, U1633107 and 61231017, National University’s Basic Research Foundation of China under Grant No. 2000300446. The work is also supported by the Foundation for Sky Young Scholars of Civil Aviation University of China.

Li, H., Xu, L. and Zhang, Z. (2017) Parameter Estimation of Maneuvering Target Using Maximum Like- lihood Estimation for MIMO Radar with Colocated Antennas. Journal of Computer and Communications, 5, 69-74. https://doi.org/10.4236/jcc.2017.53008