Beampattern synthesis with nulling for sub-arrayed MIMO radar under constant modulus constraints

Multiple input multiple output (MIMO) radars have been intensively studied for their superior performance merits compared to conventional radars including improved spatial resolution and parameter estimation. To achieve these merits, the transmitted waveforms from the MIMO transmitting antennas should be mutually orthogonal. Herein, the orthogonality is attained in the Doppler domain, namely Doppler division multiple access (DDMA), as it enjoys the simplest structure among other orthogonality schemes. Heretofore, the research in MIMO radars has focused on optimizing MIMO radar performance from different aspects including efficient waveform design, antenna beam-forming, and adaptive processing techniques. However, MIMO radars have been also a target of deliberate jamming scenarios. In this paper, the focus is turned to the evaluation of the detection performance of DDMA MIMO radars in jamming environments by creating a two-sided engagement scenario. On the jammer side, a jamming technique is proposed, Doppler-range block jamming (DRBJ), to deny the detection of a DDMA MIMO radar equipped with a moving target detector (MTD). On the radar side, a comparative detection performance analysis of two different MIMO radar detectors, normalized adaptive matched filter (NAMF) and fast 3D constant false alarm rate (CFAR), is conducted using Monte Carlo simulations. This analysis unveils divergent design philosophies of the two detectors, with each prioritizing distinct performance objectives.

Multiple Input-Multiple Output (MIMO) radar is the recent emergence of a new radar technology. This radar system is a new concept advanced for the inadequacy of the traditional system, it use spatial diversity and angel diversity to avoid multipath fading. In this paper, we mainly analyze the detection performance of MIMO radar, and at the same time compared its detection performance with phased array radar under the same conditions. This paper first established MIMO radar’s signal model based on the distribution of sources, and then analyzes the affect of radar’s detection performance through changing the number of antenna. The simulation result showed that the MIMO radar has a good detection performance compared with phased array radar in low signal-noise-ratio(SNR).

A multiple input multiple output (MIMO) radar is an emerging field which has attracted many researchers recently. In this type of radar, unlike an standard phased array radar, one can choose transmitted probing signals freely to maximize the power around the locations of the targets of interest, or more generally to approximate a given transmit beam-pattern, or to minimize the cross-correlation of the signals reflected back to the radar by the targets of interest. These signals can be correlated to each other or noncorrelated. Many papers have investigated beampattern design and waveforming in MIMO radars. One of the most famous approaches for beampattern design is named covariance based method which design cross-correlation matrix of transmitted signals instead of the signals. On the other hand, many papers have investigated beamforming of an standard phased array radar in different ways. In this paper it is desirable to design beampattern of a phased array radar by means of the MIMO radar covariance based beampattern design method, as a special case of general MIMO radar. Although many approaches are available for beamforming of phased array radar this approach would have less complexity compare to them. MATLAB software is being employed for simulations. (6 pages)

We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations.

Multiple-input multiple-output (MIMO) radars have attracted much attention for their superior ability to enhance a system's performance. In this study, the authors' goal was the study of the spatial multiplexing gain of MIMO radars with widely separated antennas (WS-MIMO), which the authors showed that is equal to the number of unambiguously detectable targets. They obtained this number from two different aspects: first, by defining the ambiguity function of a WS-MIMO radar in the case of multiple targets, suitable for such purpose; Second, by modelling the MIMO radar system with a MIMO wireless channel. They showed that a MIMO radar is indeed a MIMO wireless system communicating the information about the existence of the targets. By such modelling, they could easily make the relation between dual concepts of MIMO radar and MIMO communication, one of which is the multiplexing gain.

A multiple input multiple output (MIMO) radar system is an emerging research field which has attracted many studies in recent years. This type of radar, unlike conventional phased array radar, can transmit different probing signals via its antennas, that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar systems enable superior capabilities compared to conventional phased array radar. Many papers have introduced different ways for beamforming of MIMO radar. In this paper it is desirable to analysis some methods for beamforming of MIMO radars with planar arrays constellation and examine their 3D result beam-pattern of such constellations for covariance based MIMO radar waveforming method. MATLAB software is being employed for simulations.

Sub-arrayed multiple-input multiple-output (MIMO) radar is a new architecture of MIMO radar, which can exploit jointly the benefits of the coherent processing gain and waveform diversity, and has received extensive attention of researchers. An approach to synthesize the desired transmit beampattern for sub-arrayed MIMO radar is proposed in this paper. The essence of this approach is that the transmit beampattern is equal to the weighted sum of sub-arrays' beampatterns. First the beam-pattern of each sub-array with certain steering direction and low side lobe level is obtained by using traditional constrained optimization technique. Then under the constant total transmit energy constraint, convex optimization technique is utilized to design the optimal weight of each sub-array's beampattern, so that the synthesized beampattern can approximate the desired transmit beampattern exactly. Both analytical and simulation results validate the effectiveness of the proposed approach.

For airborne radar systems, space-time adaptive processing (STAP) is the approach that is normally adopted to detect ground moving targets in ground clutter, but the technique becomes less effective if the speed of ground moving targets is very low because of the proximity of the Doppler frequency of targets to that of ground clutter. Typical low-speed ground target detection scenarios include detecting ground troops and slowly-moving ground vehicles. Multiple-Input Multiple-Output (MIMO) radar possesses multiple transmitting and receiving channels providing additional diversified reflections for fusion processing in target detection and measurements. MIMO radar has been extensively investigated [1, 2]; but the exact structure of MIMO radar is defined widely different. In this work, an innovative multi-level MIMO radar signal processing architecture is proposed for airborne systems to effectively detect low-speed ground moving targets. The new MIMO-based approach is demonstrated to be effective for detecting such low-speed ground targets in this work, and some simulation results are presented subsequently.

We propose a new technique for multiple-input multiple-output (MIMO) radar with colocated antennas which we call phased-MIMO radar. The new technique enjoys the advantages of MIMO radar without sacrificing the main advantage of phased-array radar which is the coherent processing gain at the transmitting side. The essence of the proposed technique is to partition the transmitting array into a number of subarrays that are allowed to overlap. Then, each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. Coherent processing gain can be achieved by designing a weight vector for each subarray to form a beam towards a certain direction in space. Moreover, the subarrays are combined jointly to form a MIMO radar resulting in higher resolution capabilities. The substantial improvements offered by the proposed phased-MIMO radar technique as compared to previous techniques are demonstrated analytically and by simulations through analysis of the corresponding beampatterns and achievable output signal-to-noise-plus-interference ratios. Both analytical and simulation results validate the effectiveness of the proposed phased-MIMO radar.

The moving target detection based on compressed sending (CS) multiple-input multiple output (MIMO) radar with widely separated antennas is studied. The centralized processing is considered. The traditional centralized MIMO radar requires an exhaustive search on every possible two dimensional target velocity, resulting in huge computational complexity. In this paper, we adopt the CS technique to drastically reduce the computational burden and evaluate the reduction of the required complexity. We derive the moving target detector for the CS MIMO radar. The performance of the proposed detector is analyzed, and the receiver operating characteristic (ROC) curves are provided.

MIMO radar can provide enhanced spatial resolution and achieve better target detection performance. Hence the parameter identifiability of the system can be significantly improved. In this paper, the issue of direction of arrival (DOA) estimation in multiple-input multiple-output (MIMO) radar is discussed, and several algorithms for DOA tracking based on monostatic MIMO radar in impulsive noise background are proposed and studied. These tracking algorithms are based on the concept of robust covariation (ROC), fractional lower order moment (FLOM), fractional lower order cyclic (FLOC) and similar normalization. The transmit and receive arrays of a monostatic narrowband MIMO radar are assumed to be close to each other and eigenstructure based MUSIC algorithm at the receiver is used to identify the DOA's of the targets of interest. Simulation results verify the usefulness of the proposed algorithms. The comparison of these four tracking algorithms show that the algorithm based on the concept of similar normalization has better performance than the others.

Utilizing digital beam forming (DBF) on transmit and receive, the multiple-input multiple-output (MIMO) radar can be applied to ground moving target indication (GMTI) and can provide an efficient way to improve the GMTI performance. The operating pattern is very significant for the MIMO radar GMTI. For the traditional GMTI pattern, there is a conflict of the wider swath and narrower clutter bandwidth. The observation area can be broadened with MIMO techniques by scanning. This paper designs an effective pattern with the simultaneous transmission of multi-phase-centre multi-sub-band signals as well as beam scanning in each pulse, which provide an efficient way to settle the conflict. By beam scanning in pulse, the new pattern has wider azimuth swath, shorter revisiting period, larger coherent processing interval (CPI) number and higher SCNR. By MIMO technology, more equivalent phase centres and longer efficient baselines can be formed, so the performance of GMTI can be improved. The principle of space-time-frequency adaptive processing (STFAP) is analysed, simulation results are presented to prove the superiority of MIMO radar in clutter suppression and GMTI. Analysis of the results indicates improved detection performance with the new pattern compared to the conventional approach.

The problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple moving targets is considered in bistatic multiple input multiple output (MIMO) radar. A low complexity angle tracking algorithm in bistatic MIMO radar is proposed. The proposed algorithm derived the difference between previous and current covariance matrices. And the relationship between the different of covariance matrices and the different of target angle is derived. The performance of the proposed algorithm is improved by averaging the covariance matrix elements. Last DOD and DOA are got by least square method. This algorithm avoids the decomposition of the covariance matrix and reduces the computational complexity, which realizes DOA and DOD of the adjacent moment automatic association. The simulation results demonstrate effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Multiple Input Multiple Output (MIMO) radar is a new radar technique. It has many advantages over conventional phased radar in many ways such as anti-intercept of radar signal, low velocity target detection, and resolution. The signal transmit matrix of MIMO radar has much information such as target angle. In this paper, we analyze the signal model for MIMO radar. And then we present a new method to estimate the target angle from the matrix. At last, we show the efficiency by some simulations.

A multiple-input multiple-output (MIMO) radar system that transmits orthogonal waveforms via its antennas can achieve a greatly increased virtual aperture compared with its phased-array counterpart. This increased virtual aperture enables many of the MIMO radar advantages, including enhanced parameter identifiability and improved resolution. Practical radar requirements such as unit peak-to-average power ratio and range compression dictate that we use MIMO radar waveforms that have constant modulus and good auto- and cross-correlation properties. We present in this paper new computationally efficient cyclic algorithms for MIMO radar waveform synthesis. These algorithms can be used for the design of unimodular MIMO sequences that have very low auto- and cross-correlation sidelobes in a specified lag interval, and of very long sequences that could hardly be handled by other algorithms previously suggested in the literature. A number of examples are provided to demonstrate the performances of the new waveform synthesis algorithms.