MIMO Radar with Widely Separated Antennas
TL;DR: It is shown that with noncoherent processing, a target's RCS spatial variations can be exploited to obtain a diversity gain for target detection and for estimation of various parameters, such as angle of arrival and Doppler.
Abstract: MIMO (multiple-input multiple-output) radar refers to an architecture that employs multiple, spatially distributed transmitters and receivers. While, in a general sense, MIMO radar can be viewed as a type of multistatic radar, the separate nomenclature suggests unique features that set MIMO radar apart from the multistatic radar literature and that have a close relation to MIMO communications. This article reviews some recent work on MIMO radar with widely separated antennas. Widely separated transmit/receive antennas capture the spatial diversity of the target's radar cross section (RCS). Unique features of MIMO radar are explained and illustrated by examples. It is shown that with noncoherent processing, a target's RCS spatial variations can be exploited to obtain a diversity gain for target detection and for estimation of various parameters, such as angle of arrival and Doppler. For target location, it is shown that coherent processing can provide a resolution far exceeding that supported by the radar's waveform.
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TL;DR: A linear model for using received signal strength (RSS) measurements to obtain images of moving objects and mean-squared error bounds on image accuracy are derived, which are used to calculate the accuracy of an RTI system for a given node geometry.
Abstract: Radio Tomographic Imaging (RTI) is an emerging technology for imaging the attenuation caused by physical objects in wireless networks. This paper presents a linear model for using received signal strength (RSS) measurements to obtain images of moving objects. Noise models are investigated based on real measurements of a deployed RTI system. Mean-squared error (MSE) bounds on image accuracy are derived, which are used to calculate the accuracy of an RTI system for a given node geometry. The ill-posedness of RTI is discussed, and Tikhonov regularization is used to derive an image estimator. Experimental results of an RTI experiment with 28 nodes deployed around a 441 square foot area are presented.
838 citations
Cites background from "MIMO Radar with Widely Separated An..."
...The system discussed in this paper measures only signal strength....
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TL;DR: Various aspects of automotive radar signal processing techniques are summarized, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection.
Abstract: Automotive radars, along with other sensors such as lidar, (which stands for "light detection and ranging"), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter-wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird's-eye view to the existing research community.
705 citations
TL;DR: In this article, the authors provide a recital on the historic heritages and novel challenges facing massive/large-scale multiple-input multiple-output (LS-MIMO) systems from a detection perspective.
Abstract: The emerging massive/large-scale multiple-input multiple-output (LS-MIMO) systems that rely on very large antenna arrays have become a hot topic of wireless communications. Compared to multi-antenna aided systems being built at the time of this writing, such as the long-term evolution (LTE) based fourth generation (4G) mobile communication system which allows for up to eight antenna elements at the base station (BS), the LS-MIMO system entails an unprecedented number of antennas, say 100 or more, at the BS. The huge leap in the number of BS antennas opens the door to a new research field in communication theory, propagation and electronics, where random matrix theory begins to play a dominant role. Interestingly, LS-MIMOs also constitute a perfect example of one of the key philosophical principles of the Hegelian Dialectics, namely, that “quantitative change leads to qualitative change.” In this treatise, we provide a recital on the historic heritages and novel challenges facing LS-MIMOs from a detection perspective. First, we highlight the fundamentals of MIMO detection, including the nature of co-channel interference (CCI), the generality of the MIMO detection problem, the received signal models of both linear memoryless MIMO channels and dispersive MIMO channels exhibiting memory, as well as the complex-valued versus real-valued MIMO system models. Then, an extensive review of the representative MIMO detection methods conceived during the past 50 years (1965–2015) is presented, and relevant insights as well as lessons are inferred for the sake of designing complexity-scalable MIMO detection algorithms that are potentially applicable to LS-MIMO systems. Furthermore, we divide the LS-MIMO systems into two types, and elaborate on the distinct detection strategies suitable for each of them. The type-I LS-MIMO corresponds to the case where the number of active users is much smaller than the number of BS antennas, which is currently the mainstream definition of LS-MIMO. The type-II LS-MIMO corresponds to the case where the number of active users is comparable to the number of BS antennas. Finally, we discuss the applicability of existing MIMO detection algorithms in LS-MIMO systems, and review some of the recent advances in LS-MIMO detection.
626 citations
TL;DR: In this paper, the authors explain how the first chapter of the massive MIMO research saga has come to an end, while the story has just begun, and outline five new massive antenna array related research directions.
556 citations
TL;DR: A new method for imaging, localizing, and tracking motion behind walls in real time by taking advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network is presented.
Abstract: This paper presents a new method for imaging, localizing, and tracking motion behind walls in real time. The method takes advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network. Using a multipath channel model, we show that the signal strength on a wireless link is largely dependent on the power contained in multipath components that travel through space containing moving objects. A statistical model relating variance to spatial locations of movement is presented and used as a framework for the estimation of a motion image. From the motion image, the Kalman filter is applied to recursively track the coordinates of a moving target. Experimental results for a 34-node through-wall imaging and tracking system over a 780 square foot area are presented.
497 citations
Additional excerpts
...Manuscript received 5 Oct. 2009; revised 23 Dec. 2009; accepted 31 Mar. 2010; published online 7 Sept. 2010....
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References
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TL;DR: In this paper, the authors consider the design of channel codes for improving the data rate and/or the reliability of communications over fading channels using multiple transmit antennas and derive performance criteria for designing such codes under the assumption that the fading is slow and frequency nonselective.
Abstract: We consider the design of channel codes for improving the data rate and/or the reliability of communications over fading channels using multiple transmit antennas. Data is encoded by a channel code and the encoded data is split into n streams that are simultaneously transmitted using n transmit antennas. The received signal at each receive antenna is a linear superposition of the n transmitted signals perturbed by noise. We derive performance criteria for designing such codes under the assumption that the fading is slow and frequency nonselective. Performance is shown to be determined by matrices constructed from pairs of distinct code sequences. The minimum rank among these matrices quantifies the diversity gain, while the minimum determinant of these matrices quantifies the coding gain. The results are then extended to fast fading channels. The design criteria are used to design trellis codes for high data rate wireless communication. The encoding/decoding complexity of these codes is comparable to trellis codes employed in practice over Gaussian channels. The codes constructed here provide the best tradeoff between data rate, diversity advantage, and trellis complexity. Simulation results are provided for 4 and 8 PSK signal sets with data rates of 2 and 3 bits/symbol, demonstrating excellent performance that is within 2-3 dB of the outage capacity for these channels using only 64 state encoders.
7,105 citations
TL;DR: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver with the aim of leveraging the already highly developed 1-D codec technology.
Abstract: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n T , n R ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.
6,812 citations
"MIMO Radar with Widely Separated An..." refers background in this paper
...The other gain is called spatial multiplexing [23]....
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...MIMO systems have led to a revolution in wireless communications [23]....
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Book•
01 Jan 1962
TL;DR: This chapter discusses Radar Equation, MTI and Pulse Doppler Radar, and Information from Radar Signals, as well as Radar Antenna, Radar Transmitters and Radar Receiver.
Abstract: 1 An Introduction to Radar 2 The Radar Equation 3 MTI and Pulse Doppler Radar 4 Tracking Radar 5 Detection of Signals in Noise 6 Information from Radar Signals 7 Radar Clutter 8 Propogation of Radar Waves 9 The Radar Antenna 10 Radar Transmitters 11 Radar Receiver
6,010 citations
"MIMO Radar with Widely Separated An..." refers methods in this paper
...Beamforming at the receiver in the direction θ0, we obtain at the output of the beamformer r(t) = ∑N =1 a∗ (θ0)r (t), which is the model for the received signal in conventional array radars [26]....
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...Frequency diversity has been applied to decorrelate RCS response of complex targets, and high resolution location estimation is possible with wideband waveforms [26]....
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...If the RCS fluctuations are fixed during an antenna scan, but vary independently from scan to scan, our target model represents a classical Swerling case I (which represents a target in slow motion) [26]....
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26 Apr 2004
TL;DR: It is shown that MIMO radar leads to significant performance improvement in DF accuracy, and is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction.
Abstract: It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radar's performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.
1,437 citations
"MIMO Radar with Widely Separated An..." refers background in this paper
...For sufficiently separated receive antennas, it can be shown that rank K = N [15], [20]....
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...As such, it has parallels with multiple-input multiple-output (MIMO) systems in wireless communications, and subsequent publications have adopted the “MIMO radar” nomenclature for radar systems with cooperating transmitters [12]–[15]....
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...It can be shown that the matrix H can be expressed [15]...
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...The loss of processing gain compared to conventional phased-array beamforming due to the uniform illumination is compensated by the gain in time, since a narrow beam does not need to be scanned [15]....
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TL;DR: The optimal detector in the Neyman–Pearson sense is developed and analyzed for the statistical MIMO radar and it is shown that the optimal detector consists of noncoherent processing of the receiver sensors' outputs and that for cases of practical interest, detection performance is superior to that obtained through coherent processing.
Abstract: Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this proposal introduces the statistical MIMO radar concept To the authors' knowledge, this is the first time that the statistical MIMO is being proposed for radar The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while statistical MIMO radar capitalizes on the diversity of target scattering to improve radar performance Coherent processing is made possible by highly correlated signals at the receiver array, whereas in statistical MIMO radar, the signals received by the array elements are uncorrelated Radar targets generally consist of many small elemental scatterers that are fused by the radar waveform and the processing at the receiver, to result in echoes with fluctuating amplitude and phase It is well known that in conventional radar, slow fluctuations of the target radar cross section (RCS) result in target fades that degrade radar performance By spacing the antenna elements at the transmitter and at the receiver such that the target angular spread is manifested, the MIMO radar can exploit the spatial diversity of target scatterers opening the way to a variety of new techniques that can improve radar performance This paper focuses on the application of the target spatial diversity to improve detection performance The optimal detector in the Neyman–Pearson sense is developed and analyzed for the statistical MIMO radar It is shown that the optimal detector consists of noncoherent processing of the receiver sensors' outputs and that for cases of practical interest, detection performance is superior to that obtained through coherent processing An optimal detector invariant to the signal and noise levels is also developed and analyzed In this case as well, statistical MIMO radar provides great improvements over other types of array radars
1,413 citations
"MIMO Radar with Widely Separated An..." refers background or methods in this paper
...With widely separated antennas, MIMO radar has the ability to improve radar performance by exploiting RCS diversity [20], handle slow moving targets by exploiting Doppler estimates from multiple directions [21], and support high resolution target localization [22]....
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...Such targets display essentially independent scattering returns when radiated from sufficiently different directions (see [20] for a mathematical illustration of this using a reasonable model)....
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...In [20], it is shown that, if Q is large, all the channel elements h k are jointly Gaussian with zero mean and unit variance....
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...For a more extensive set of results we refer the reader to [20]....
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...Closed-form performance expressions are given in [20] for cases with full and partial model knowledge....
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