A scheme for multitarget identification and localization using bistatic MIMO radar systems is proposed. Multitarget can be distinguished by Capon method, as well as the targets angles with respect to transmitter and receiver can be synthesized using the received signals. Thus, the locations of the multiple targets are obtained and spatial synchronization problem in traditional bistatic radars is avoided. The maximum number of targets that can be uniquely identified by proposed method is also analyzed. It is indicated that the product of the numbers of receive and transmit elements minus-one targets can be identified by exploiting the fluctuating of the radar cross section (RCS) of the targets. Cramer-Rao bounds (CRB) are derived to obtain more insights of this scheme. Simulation results demonstrate the performances of the proposed method using Swerling II target model in various scenarios.

Phased array is widely used in radar systems with its beam steering fixed in one direction for all ranges. Therefore, the range of a target cannot be determined within a single pulse when range ambiguity exists. In this paper, an unambiguous approach for joint range and angle estimation is devised for multiple-input multiple-output (MIMO) radar with frequency diverse array (FDA). Unlike the traditional phased array, FDA is capable of employing a small frequency increment across the array elements. Because of the frequency increment, the transmit steering vector of the FDA-MIMO radar is a function of both range and angle. As a result, the FDA-MIMO radar is able to utilize degrees-of-freedom in the range-angle domains to jointly determine the range and angle parameters of the target. In addition, the Cramér-Rao bounds for range and angle are derived, and the coupling between these two parameters is analyzed. Numerical results are presented to validate the effectiveness of the proposed approach. Index TermsMultiple-input multiple-output radar; frequency diverse array; range ambiguity; joint range and angle estimation;Cramér-Rao bound I. INTRODUCTIONAs multiple-input multiple-output (MIMO) radar [1]-[3] is a flexible technique which enjoys many advantages without sacrificing the excellence of the phased-array radar, it has recently received much attention. Unlike the traditional phased-array radar, the MIMO radar is able to efficiently employ the degrees-of-freedom (DOFs) in the temporal domain by emitting orthogonal waveforms and spatial domain by utilizing the array structure in transmit and receive antennas. This eventually leads to considerable enhancement in identifiability and resolution. Basically, , IEEE Transactions on Signal Processing 2 there are two types of MIMO radar, that is, colocated MIMO radar [1] and distributed MIMO radar [2]. This work addresses the colocated MIMO radar.One of the foremost tasks of radar system is target localization for military or civilian purposes [4]. Each target is characterized by its range, angle, velocity and reflected complex amplitude. The phased-array radar can provide high-resolution angle estimation and thereby is widely used for target localization. It is known that by increasing the pulse repetition frequency (PRF) of radar, higher levels of clutter cancellation can be achieved and Doppler ambiguities can be eliminated. However, an increase in PRF may result in the maximum unambiguous range much smaller than the desired operating range [5]. The limitation of phased array is that its beam steering is fixed in only one direction for all ranges. Thus, the ranges of targets cannot be directly estimated from its beamforming output for high PRF radar in the presence of the inherent range ambiguity. A multiple PRF radar is utilized in [5], [6] to resolve the range ambiguity problem. In the multiple-target case, however, the ghost targets will appear when the range partnership errors exist. The staggered PRF and pulse-diverse waveform strategies could also mitigate the ran...

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: A computationally e cient method for two-dimensional direction-of-arrival estimation of multiple narrowband sources impinging on the far eld of a planar array i s p r esented. The key idea is to apply the propagator method which only requires linear operations but does not involve a n y eigendecomposition or singular value decomposition as in common subspace techniques such as MUSIC and ESPRIT. Comparing with a fast ESPRIT-based algorithm, it has a lower computational complexity particularly when the ratio of array size to the number of sources is large, at the expense of negligible performance loss. Simulation results are included to demonstrate the performance of the proposed technique.

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