## What is/are Mimo Radar?

Mimo Radar - In this paper, we provide a broad overview of tensor analysis in wireless communications and MIMO radar.^{[1]}A numerical simulation has been conducted to prove the proposed technique and the results have shown that bi-directional phased-MIMO antenna array is an excellent candidate for future phased-MIMO radar systems.

^{[2]}The article presents the results of a MIMO radar energy efficiency study for various transmitter configurations.

^{[3]}However, MIMO radar fundamentally suffers from a notable signal-to-noise ratio (SNR) loss compared to an ideal phased-array (PA) radar.

^{[4]}In the previous works, the MC effects in MIMO radar are always modeled with direction-independent MC matrices, which may not be guaranteed in practice.

^{[5]}In this paper, we consider the waveform design problem for a joint multiuser MIMO communication and MIMO radar system.

^{[6]}The main thrust is to estimate direction-of-arrival (DOA) via MIMO radar.

^{[7]}The FDA-MIMO radar, a hybrid of FDA and MIMO radar, can be used for target parameter estimation.

^{[8]}To illustrate the improvement in the performance of priority access license (PAL) and general authorized access (GAA) users in an IBFD-assisted CBRS, we consider a CBRS mobile broadband network (MBN) architecture comprising an incumbent in the form of a MIMO radar system and an IBFD MIMO MBN, consisting of PAL and GAA users.

^{[9]}In this paper, we propose an image metric-based autofocus algorithm to address the SAR image focusing challenge associated with the Ka frequency band, our MIMO radar configuration and forward-looking 3-D geometry.

^{[10]}In the IRS-aided DMIMO radar systems, each IRS is controlled by its receiver, and the receivers can receive the signals reflected from the target and the IRS simultaneously.

^{[11]}MIMO radar sensors with a 3-dimension detection zone are recently used for safety-related sensors.

^{[12]}MIMO radar sensors rely on strictly orthogonal signals to distinguish between multiple transmitters (TX).

^{[13]}By utilizing the uniformity of the subarrays in coprime EMVS–MIMO radar, the rotation invariant technique is adopted to achieve ambiguous elevation angle estimation.

^{[14]}Direction of arrival (DOA) in MIMO radar is estimated from the phase differences between its channels.

^{[15]}With the development of application requirements of the MIMO radar, it is necessary to further improve the angular resolution under the certain number of antennas and the certain physical aperture.

^{[16]}Compared to the single-waveform design for conventional radars, the multi-waveform design enables extra degrees of freedom (DOFs) for modern radars, which therefore triggers a series of relevant studies on MIMO radar.

^{[17]}In this paper, the method of transmitting interference suppression for MIMO radar with frequency division multiplexing is studied and discussed.

^{[18]}A MIMO radar simulator is proposed to estimate the coherent ambiguity function in 3D multi-target multi-band scenarios.

^{[19]}Performance of MIMO radar system can be improved using newly developed bio inspired metaheuristic algorithms as compared to conventional and adaptive beamforming algorithms.

^{[20]}Through simulations, it is shown that with a sparse transmit and receive array, an improvement in beam-width and side-lobe levels in the virtual array patterns for MIMO radars can be achieved.

^{[21]}Simulation examples demonstrate that the proposed algorithm has the advantage of lower computational complexity compared with the existing cyclic algorithms (CA) and primal dual type algorithm (PDT) for MIMO radar waveform design.

^{[22]}In this mode, a completely defocused beam is transmitted and a focused receive beam is synthesized so that the MIMO radar is capable of tracking targets independently.

^{[23]}MIMO radar obtains a larger aperture with fewer arrays.

^{[24]}The effects of such sources are analysed with a MIMO radar model using time-division multiplexed (TDM) frequency modulated waveforms.

^{[25]}Conventional transmit subarray partitioning schemes of phased-MIMO radar will cause several problems, the reduction of array aperture, the increase of feeding network complexity and optimization algorithms time cost.

^{[26]}Though the refined maximum likelihood (RML) algorithm can be directly applied to low angle estimation in MIMO radar, its computational burden is huge due to the large virtual aperture.

^{[27]}The experimental results of DOFs, VAA, number of resolvable sources, Cram $$\acute{\hbox {e}}$$ e ´ r–Rao bound performance, detection, and resolution ability reveal that the proposed sensor array design approach is suitable for MIMO radar which is also capable of estimating the DOAs of multiple sources efficiently in underdetermined scenarios.

^{[28]}In EPC-MIMO radar, a novel phase modulation is performed in the joint transmit element and pulse domain, resulting in an equivalent spatial frequency offset corresponding to different pulses.

^{[29]}Nonidentical pulse (NP) processing, a component of waveform diversity, has been the subject of much research due to its potentially transformative impact on technologies such as radar-embedded communications, electronic protection, MIMO radar, multi-mission radar and many others.

^{[30]}In this paper, we investigate the joint optimization of the waveform covariance matrix and the antenna position vector for a MIMO radar system to approximate a given transmit beam-pattern, as well as to minimize the cross-correlation of the received waveforms reflected back from the targets.

^{[31]}A MIMO radar based ego-motion estimation scheme is presented.

^{[32]}Frequency-hopping (FH) MIMO radar is recently introduced as an underlying system for realizing dual-function radar-communication (DFRC), increasing communication symbol rates to multiples of the radar pulse repetition frequency.

^{[33]}This paper deals with the design of the constant modulus sequence set for MIMO radar in an effort to achieve the desired correlation properties and favorable Doppler tolerance.

^{[34]}A data-driven robust DOA estimation framework is proposed for MIMO radar via deep neural networks (DNN), so as to overcome the problems mentioned before.

^{[35]}Previous work that embeds communication symbols into the emission of MIMO radar with orthogonal FH waveforms via phase modulation, and waveform orthogonality compromises the transmit processing gain of the radar.

^{[36]}Each symbol is represented by a phase modulated pulse code sequence which multiplies the radar hops in fast-time before transmitted from the MIMO radar platform.

^{[37]}Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary.

^{[38]}Moreover, the mathematical formula derivation and numerical results verify the performance of the proposed algorithm, which shows that TMRC-FDA-MIMO radar system is superior to others mentioned above.

^{[39]}We present a digital beamforming approach using the MIMO radar, with a range resolution of 6.

^{[40]}The considered system is referred to as an airborne TS-MIMO radar, whose transmit array is divided into several subarrays to form the steerable waveforms with directional gain.

^{[41]}, high directional coherent gain, and the main advantage of the MIMO radar, i.

^{[42]}This study reports the ability of Phased-MIMO radars to be able to distinguish two or more objects that are close known as angular resolution of radar.

^{[43]}In this paper, we propose a MIMO radar aided channel estimation scheme using deep learning (DL) for the uplink mmWave multiuser (MU)-MIMO communications.

^{[44]}FDA-MIMO radar is a novel array structure which employs the small frequency offset across the transmit waveform to produce the range-angle dependent beampattern.

^{[45]}Therefore, the ambiguity of sparse array in MIMO radar can be cleared.

^{[46]}To reduce the complexity of the system and improve CRB performance at the same time, in this paper, the virtual array of MIMO radar is designed directly by selecting outputs from matched filters at the receive side.

^{[47]}The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars.

^{[48]}Then we deduce the application of generalized MUSIC algorithm and maximum likelihood estimation algorithm for MIMO radar in the accurate terrain signal model.

^{[49]}This paper proposes a towed jamming suppression method based on FDA-MIMO radar.

^{[50]}

## multiple input multiple

In contrast to time-division multiplexing (TDM) multiple-input multiple-output (MIMO) radars, in which only a single transmitter is active at a time in the TDM MIMO radar configuration due to the working principle of switching between different transmitting elements, here, all the phased array transmitters of the proposed radar work simultaneously.^{[1]}The monostatic FDA and multiple-input-multiple-output (FDA-MIMO) is a research hotspot in parameter estimation field, but the research based on bistatic FDA-MIMO radar is insufficient.

^{[2]}We propose a co-located polarization multiple-input multiple-output (MIMO) radar system that combines the advantages of MIMO radar and those offered by optimally choosing the transmit polarization to improve the jamming suppression performance.

^{[3]}Aiming at the problem of large amount of calculation and long recognition time of traditional method of modulation identification of centralised multiple-input multiple-output (MIMO) radar signal, partial zero-delay instantaneous autocorrelation spectrum is proposed to identify the modulation of centralised MIMO radar here.

^{[4]}

## frequency diverse array

Based on the unique range-dependent beampattern of the frequency diverse array (FDA)-MIMO radar, we propose a novel robust mainlobe deceptive target suppression method based on covariance matrix reconstruction to form nulls at the frequency points of the transmit–receive domain where deceptive targets are located.^{[1]}In recent years, frequency diverse array (FDA) with multiple-input multiple-output (MIMO) technique, which is referred to as FDA-MIMO radar, has attracted extensive attentions due to its outstanding advantages of introducing additional controllable degrees-of-freedom (DOFs) in range dimension.

^{[2]}Hybridization of a frequency diverse array (FDA) generated range-angle-time dependent beampattern with multiple input multiple output (MIMO) radar waveform diversity, namely, FDA-MIMO radar, provides more degrees-of-freedom to improve overall system performance.

^{[3]}Here, frequency diverse array (FDA) MIMO radar is investigated for low-observable moving target detection.

^{[4]}

## interference plus noise

In this paper, using multiple FMCW MIMO radar sensors, we intend to investigate the effect of interference on victim in terms of signal-to-interference-plus-noise ratio.^{[1]}This paper considers the waveform design for colocated MIMO radar to improve target detectability embedded in signal-dependent interferences, and maximize the SINR (signal-to-interference-plus-noise ratio).

^{[2]}In this paper, we examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxSINR) beamforming at the MIMO radar receiver.

^{[3]}Radar performance in terms of transmit-receive gain, SINR (Signal-to-Interference-plus-Noise-Power Ratio), and maximum range has been formulated and its effectiveness has been compared to Phased Array (PA), MIMO, and PMIMO radars.

^{[4]}

## target detection performance

In this paper, we design a MIMO radar transmit matrix to improve target detection performance in the presence of interference.^{[1]}Motivated by the improved capacity and energy performance by intelligent reflecting surface (IRS) in multiinput–multioutput (MIMO) communication systems, we apply the IRS in the colocated MIMO radar systems to increase the received power and improve the target detection performance.

^{[2]}In this paper, we aim at the problem that MIMO radar’s target detection performance is greatly reduced in the complex multi-signal-dependent interferences environment.

^{[3]}

## plus noise ratio

In this paper, the signal-to-ambiguous-plus-noise ratio (SANR) is introduced to evaluate the range ambiguity resolvability of the EPC-MIMO radar, where targets in different range regions can be separated effectively through conventional beamforming algorithm under ideal conditions.^{[1]}

## Distributed Mimo Radar

To this end, we present a general signal model for distributed MIMO radar, examine target detection using existing coherent/non-coherent detectors and two new detectors, including a hybrid detector that requires phase coherence locally but not across distributed antennas, and provide a statistical analysis leading to closed-form expressions of false alarm and detection probabilities for all detectors.^{[1]}In this paper, a new algorithm using bistatic range measurements is developed for target localization in distributed MIMO radars.

^{[2]}Simulation results show that our proposed algorithms are efficient methods for transmitter and receiver placement in distributed MIMO radar systems.

^{[3]}We aim to enhance the system surveillance and localization performance in different subareas by optimizing antenna positions, with metrics being formulated to evaluate the surveillance and localization performance of distributed MIMO radar systems.

^{[4]}In this letter, an efficient method for solving the multi-target localization problem in distributed MIMO radars is proposed.

^{[5]}The ACD neglects the cross correlation of the radar waveforms, which may be significant in distributed MIMO radar.

^{[6]}In this paper, an effective joint beam selection and power allocation (JBSPA) method is proposed to solve the online resource scheduling problem for multi-target tracking in distributed MIMO radar system.

^{[7]}In this letter, we investigate how to use deception bistatic range measurements to estimate the target location and deception ranges, and propose a message passing based method for target localization under range deception jamming in distributed MIMO radar.

^{[8]}In this paper, the problem of target localization and clock synchronization in distributed MIMO radar systems in presence of time synchronization errors is addressed by utilizing time delay measurements.

^{[9]}Based on this natural sparsity, in this paper we introduce a block-sparse illustration model for distributed MIMO radar and propose a completely unique block-sparse recovery algorithmic rule supported approximate l0 norm diminution.

^{[10]}Distributed MIMO radar system configured with the DTFR (defocused transmit-focused receive) mode can detect and track multiple targets.

^{[11]}We propose cooperative passive coherent location (CPCL), a distributed MIMO radar service, which can be offered by mobile radio network operators as a service for public user groups.

^{[12]}

## Bistatic Mimo Radar

In order to solve this problem, a low interception bistatic MIMO radar with improved coprime array is proposed in this paper.^{[1]}A computationally efficient preprocessing technique for the estimation of coherent angles of targets for the bistatic MIMO radar centered on Toeplitz based Matrix compression algorithm is presented.

^{[2]}This paper focuses on the direction-of-departure (DOD) and direction-of-arrival (DOA) problem in bistatic MIMO radar with unknown gain-phase errors (GPE).

^{[3]}Thus, this paper aims to leverage the benefits of TF analysis to the estimation of DOD and DOA jointly for a bistatic MIMO radar by using Spatial Time-Frequency Distribution (STFD) matrices.

^{[4]}In this paper, the aim is to present an efficient method to achieve an improved estimation of the joint direction of departure (DOD) and direction of arrival (DOA) for the bistatic MIMO radar with an unknown ‘Toeplitz’ colored noise effect.

^{[5]}This paper deals with a bistatic MIMO radar system where the targets are located in the near-field region.

^{[6]}In this paper, we address the problem of gridless DOD and DOA estimation in bistatic MIMO radar, and develop a multiple-snapshot 2D-ANM algorithm and its two low complexity versions.

^{[7]}In this paper, we investigate into the problem of target localization in bistatic MIMO radar system with the prototype of arbitrary EMVS.

^{[8]}In this paper, recognition issue of range deception jamming is considered for bistatic MIMO radar systems.

^{[9]}In this paper, we investigate the problem of joint direction of departure (DOD) and the direction of arrival (DOA) estimation in bistatic MIMO radar.

^{[10]}In this paper, a joint transmit-receive beamspace parallel factor (B-PARAFAC) method is proposed for angle estimation in bistatic MIMO radar.

^{[11]}

## Fmcw Mimo Radar

Finally, we leverage these advantages of combining both RDMA and DDMA to balance the performance for FMCW MIMO radar in angular resolution, unambiguous range, and unambiguous velocity.^{[1]}In this paper, using multiple FMCW MIMO radar sensors, we intend to investigate the effect of interference on victim in terms of signal-to-interference-plus-noise ratio.

^{[2]}Initially, the mathematical signal model for a Slow-Time Phase-Coded (ST-PC) FMCW MIMO radar is derived where it is shown that proper decoding of received returns for moving targets requires phase compensation of induced doppler shifts.

^{[3]}In this article, to get a high-resolution radar image with distributed frequency modulated continuous waveform multiple-input–multiple-output (FMCW MIMO) radar, Bayesian matching pursuit (BMP)-based imaging methods are proposed, in which the received signals at the distributed FMCW MIMO radars are reformulated in terms of the (azimuth, range) patches in the image region of interest and the maximum a posterior (MAP) estimator that can estimate the azimuth angles and ranges of multiple targets is then derived.

^{[4]}Fast chirp FMCW MIMO radar with inter-chirp coding provides high emission power by utilizing simultaneous antennas transmissions.

^{[5]}In this study, a 77 GHz FMCW MIMO radar system is presented.

^{[6]}This work presents a compact 76-to-81GHz FMCW MIMO radar with fast chirp generation and integrated with an AiP array in embedded glass fan-out (eGFO) technology for short and ultra-short range application.

^{[7]}The distance is arbitrary and this will enable us to increase the number of radars in coherent FMCW MIMO radar networks in the future.

^{[8]}

## Colocated Mimo Radar

In this paper, given communication channels, we directly optimize constant-modulus transmit waveforms for a colocated MIMO radar, such that those communication sinks can decode the data stream in their own manner.^{[1]}Different from traditional colocated MIMO radar, space-time coding array (STCA) transmits an identical waveform with a tiny time delay circulating across array elements.

^{[2]}Motivated by the improved capacity and energy performance by intelligent reflecting surface (IRS) in multiinput–multioutput (MIMO) communication systems, we apply the IRS in the colocated MIMO radar systems to increase the received power and improve the target detection performance.

^{[3]}This paper considers the waveform design for colocated MIMO radar to improve target detectability embedded in signal-dependent interferences, and maximize the SINR (signal-to-interference-plus-noise ratio).

^{[4]}However, the estimation performance of the direction of arrivals (DOAs) and the direction of departures (DODs) will be significantly degraded for a colocated MIMO radar system with unknown mutual coupling matrix (MCM).

^{[5]}In this letter, we consider the direction-of-arrival (DOA) estimation problem in colocated MIMO radar with imperfect waveforms, and a new methodology is presented.

^{[6]}This work focuses on target detection in a colocated MIMO radar system.

^{[7]}

## Coherent Mimo Radar

In this paper, we propose to use fuzzy fusion rules to improve the performances of the CA-CFAR and OS-CFAR detectors for non-coherent MIMO radars in homogenous and non-homogenous Pareto background.^{[1]}It is shown that the coherency gain of coherent MIMO radar is greater than the non-coherent one, while the geometry gain of coherent MIMO radar is always smaller than or equal to the non-coherent case.

^{[2]}The paper considers the system of synchronization of positions of small base spatially coherent MIMO radar system based on surveillance radars with mechanical rotation.

^{[3]}

## Collocated Mimo Radar

In this paper, an efficient power allocation (PA) strategy is developed for maneuvering target tracking (MTT) in the collocated MIMO radar.^{[1]}Therefore, different targets may be illuminated simultaneously with one beam in the collocated MIMO radar, providing greater freedom degree in resource management.

^{[2]}Aiming at the problem of scattering centers resolving and angular positions estimation of spatially extended targets, a high-resolution and high-accuracy angle estimation method based on multi-task group sparse model and collocated MIMO radar is proposed, which is helpful to obtain the structure information of targets and improve the success rate of target recognition.

^{[3]}

## Uwb Mimo Radar

In the proposed framework, first, we use UWB MIMO radar to capture the human body information.^{[1]}In this paper we provide a short discussion of the science requirements and conceptual design of a constellation of CubeSats with UWB MIMO radars for sounding ice and mapping of lava tubes.

^{[2]}This paper proposes an approach of multiple stationary targets localization based on data association using UWB MIMO radar with one transmitting and two receiving antennas.

^{[3]}

## Monostatic Mimo Radar

In this paper, we consider the problem of two-dimensional (2-D) direction of arrival (DOA) estimation for L-shaped monostatic MIMO radar with two-level nested linear array (NLA).^{[1]}A gridless sparse reconstruction technology is applied to monostatic MIMO radar DOA estimation.

^{[2]}Due to redundancy of the received data of monostatic MIMO radar, the computational complexity of the inversion of the covariance matrix is increased.

^{[3]}

## Array Mimo Radar

Aiming at the problems of low degree of freedom, small array aperture, and phase ambiguity in traditional coprime array direction-of-arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed.^{[1]}Aiming at the problem that traditional direction of arrival (DOA) estimation methods cannot handle multiple sources with high accuracy while increasing the degrees of freedom (DOF), a new method for 2-D DOA estimation based on coprime array MIMO radar (SA-MIMO-CA) is proposed.

^{[2]}Aiming at the problems of low degree of freedom, small array aperture, phase ambiguity and other problems of traditional coprime array direction of arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed.

^{[3]}

## Passive Mimo Radar

In this article, we show that the preamble information can be exploited to improve the performance of passive MIMO radar.^{[1]}In the passive MIMO radar, the transmitted signals of illuminators of opportunity are totally unknown, and the received signals are contaminated by the colored Gaussian noise with an unknown covariance matrix.

^{[2]}In this paper, we develop a new algorithm for centralized target detection in passive MIMO radar (PMR) using sparse recovery technique.

^{[3]}

## Imaging Mimo Radar

The novelty of the paper comes from deriving a flexible waveform design problem applicable for the emerging 4D imaging MIMO radars with application to automotive radar systems.^{[1]}This way, the novel method allows for a simple but yet effective calibration of fully polarimetric high resolution near field imaging MIMO radars based on two cost-efficient passive standards and with very low adjustment efforts during the calibration.

^{[2]}

## Ghz Mimo Radar

The algorithm concept is both simulated and tested with a 78 GHz MIMO radar system.^{[1]}We propose a convolutional neural network (CNN)which classifies the type and direction of a stationary object from the range-Doppler map acquired by a 79 GHz MIMO radar.

^{[2]}

## Centralized Mimo Radar

This analysis proceeds in parallel with the running progresses of microwave photonics (MWP), which could represent, in the near future, a new paradigm for the development of centralized MIMO radar architectures.^{[1]}The distance between receiving antennas and transmitting antennas is very small in centralized MIMO radars, which is easy to place together.

^{[2]}

## Photonic Mimo Radar

This microwave photonic MIMO radar can have a large operation bandwidth and a large equivalent aperture, which helps to achieve high-resolution imaging in both range and azimuth directions.^{[1]}The broadband microwave photonic MIMO radar based on optical wavelength division multiplexing technology was introduced and its performance in target detection and imaging was analyzed.

^{[2]}

## Coprime Mimo Radar

Compared to the existing uniform linear array, coprime MIMO radar is occupying large array aperture, and the proposed algorithm does not need to obtain signal subspace by eigendecomposition.^{[1]}In this paper, a new technology based on average processing of redundant virtual array elements is proposed for coprime MIMO radar direction of arrival (DOA) estimation.

^{[2]}

## Nested Mimo Radar

Compared with the existing nested MIMO radar, the proposed MIMO array configuration not only has closed-form expressions for sensors’ positions and the number of maximum DOF, but also significantly improves the array aperture.^{[1]}Finally, we derive the coarray Cramér–Rao Bound (CRB) for the nested MIMO radar, and also conduct a study for the conditions under which the CRB exists.

^{[2]}

## Tdm Mimo Radar

The TDM MIMO radars create orthogonal probing signals (in time domain) by allocating a transmitter to a separate time slot.^{[1]}In contrast to time-division multiplexing (TDM) multiple-input multiple-output (MIMO) radars, in which only a single transmitter is active at a time in the TDM MIMO radar configuration due to the working principle of switching between different transmitting elements, here, all the phased array transmitters of the proposed radar work simultaneously.

^{[2]}

## Multiplexing Mimo Radar

In view of the complex electromagnetic environment faced by the traditional meter wave radar, especially the forward main lobe jamming which is highly correlated with the radar emission waveform, the target, jamming and multipath echo models of the proposed METER wave frequency division multiplexing MIMO radar are established and quantitative analysis is carried out.^{[1]}Time-division multiplexing MIMO radar is configured at 80 GHz in a multitarget scenario for DoA estimation, and the targets are distinguished with 25° effective angular resolution.

^{[2]}

## Power Mimo Radar

However, implementing a low cost low power MIMO radar is challenging.^{[1]}However, implementing a low cost low power MIMO radar is challenging.

^{[2]}