Physical Antennas Research Articles

High‐accuracy DOA estimation via parallel sparse nested array with extended aperture and reduced mutual coupling

AbstractThis letter proposes a novel parallel sparse nested array and then provides a matrix reconstruction‐based method with three steps, to enhance the performance of direction of arrival (DOA) estimation in practice. The spacings between the closest antennas along x‐ and y‐axes, are coprime and much greater than half‐wavelength in the proposed array, which contributes to efficiently eliminate the mutual coupling and achieve larger aperture with limited physical antennas. By using the oblique projection operator with iteration, the proposed method can employ all items of covariance matrix of the received data to construct a virtual covariance matrix with increased degrees of freedom, for effectively improving angle estimation performance. Then the unique and high‐accuracy DOA estimation is obtained via the coprime‐ness. The simulation results show the superiority of the proposed array and method for DOA estimation in the presence of mutual coupling and limited antennas.

Automotive SAR imaging: potentials, challenges, and performances

Abstract The main interest in using synthetic aperture radar (SAR) technology in automotive scenarios is that arbitrarily long arrays can be synthesized by exploiting the natural motion of the ego vehicle, enabling finer azimuth resolution and improved detection. All of this is achieved without increasing the hardware complexity in terms of the number of physical antennas. In this paper, we start by discussing the application of SAR imaging in the automotive environment from both theoretical and experimental perspectives. We proceed by describing an efficient processing workflow and we derive the rough number of operations required to focus an image proving the real-time imaging capability of the system. The experimental results are based on open road data acquired using an eight-channel radar at 77 GHz, considering side-looking SAR and forward SAR. The results confirm the idea that SAR imaging can be successfully and routinely used for high-resolution mapping of urban environments in the near future.

Efficient DOA and Polarization Estimation for Dual-Polarization Synthetic Nested Arrays

To obtain a larger aperture for improving parameter estimation performance, we present a novel polarization sensitive array with dual-polarization synthetic nested structure, and then propose a low-complexity method for direction of arrival (DOA) and polarization estimation with two steps. There is a systematic procedure to determine the number and positions of antennas in each single-polarization subarray used for the synthetic nested array, in order to achieve more degrees of freedom (DOFs) and larger aperture for difference coarray with limited physical antennas. The increased DOFs of cross- and self-difference coarrays are quantitatively provided. To handle underdetermined parameter estimation with the resulting DOFs, the proposed method first estimates initial DOA and polarization state by using root-MUSIC and oblique projection operator, based on hole-free cross-difference coarray from cross-correlation matrix between subarrays. In the second step, holes in self-difference coarray, which is from autocorrelation matrix of single-polarization subarray, are filled with initial estimation. By exploiting both hole-free self- and cross-difference coarrays, an efficient search-based algorithm with initially estimated parameters is explored for refined estimation. The Cramér–Rao bound for the array and computational complexity of the method are provided. Simulation results are given to demonstrate the superior performance of the proposed array and method.

Synthetic sparse nested array with extended aperture and reduced mutual coupling for DOA estimation

To obtain a larger aperture for improving direction of arrival (DOA) estimation performance, we present a synthetic sparse nested array consisting of three subarrays with dual-polarization antennas, and then propose a cascade method composing of three steps for super-resolution angle estimation with range of 180 degree. There is a systematic procedure to determine the number and positions of antennas in each single-polarization subarray used for the synthetic sparse nested array, in order to efficiently reduce mutual coupling and obtain increased degrees of freedom and aperture for difference coarray with limited physical antennas. By exploiting the configuration and fully utilizing the aperture of the proposed array, two sparse uniform linear arrays are achieved in difference coarray domain, for giving coarse estimation and fine but ambiguous estimation in the first and second steps, respectively. Then an automatic pair matching based on pseudo ambiguous angles is provided to obtain unique DOA estimation in the third step. Theoretical analysis and simulation results are given to demonstrate the superiority of the proposed array and method for high-accuracy DOA estimation in the presence of mutual coupling.

Development of a Mathematical Model for Multi-user Coded-Cooperation Based Cognitive Radio System and Its Outage Probability Analysis

In this paper, mathematical system model for a single and multi-user coded-cooperation-based cognitive radio system is developed. In this model, both source and relay are communicating to a single destination with the help of each other. Further, all possible multi-user scenarios are developed and their end-to-end outage probability (Pout) is calculated for the underlay mode of cognitive radio. The performance of the system is analyzed in the form of channel gain and interference temperature constraint for the Rayleigh fading channel. The proposed system concludes that the coded cooperation with cognitive radio outperforms the available techniques in the form of bandwidth, diversity, spectrum utilization efficiency and thus improving the quality of communication. Furthermore, the theoretical analysis of the outage probability for both system models is validated by asymptotic analysis. The proposed system can be set as a standard for all those cognitive radio applications which require better spectrum efficiency even if there is a scarcity of multiple physical antennas.

Classification-Based One-Bit DOA Estimation for Sparse Arrays

Nowadays, high-resolution DOA estimation techniques have been widely used in many fields such as sonar, communication, radio astronomy and biomedicine etc. Unfortunately, conventional algorithms cannot achieve high precision due to the limitation of the array aperture, and usually suffer from high computational complexity. In this paper, we innovatively model the DOA estimation problem of incoherent signals as a binary classification problem and greatly reduce physical complexity by virtue of sparse arrays. We first propose a classification framework for DOA estimation by benefiting from one-bit quantification. In this framework, any classification algorithm can be exploited to estimate DOA, such as logistic regression used in this paper. And then, sparse array is considered to reduce the exceeding number of antennas. Moreover, an iterative grid refinement procedure is presented to achieve more accurate DOA estimation and further reduces the actual number of physical antennas. Simultaneously, we derive Cramer-Rao bound (CRB) for the proposed algorithm. Finally, simulations are conducted for correctness and validation and the results illustrate the significant performance and reduction of complexity in hardware and computation over the existing methods.

High Fidelity Physics Simulation of 128 Channel MIMO Sensor for 77GHz Automotive Radar

Automotive radar is one of the enabling technologies for advanced driver assistance systems (ADAS) and subsequently fully autonomous vehicles. Along with determining the range and velocity of targets with fairly high resolution, autonomous vehicles navigating complex urban environments need radar sensors with high azimuth and elevation resolution. Size and cost constraints limit the physical number of antennas that can be used to achieve high resolution direction-of-arrival (DoA) estimation. Multiple-input/multiple-output (MIMO) schemes achieve larger virtual arrays using fewer physical antennas than would be needed for a single-input/multiple-output (SIMO) system. This paper presents a high-fidelity physics simulation of a 77GHz, frequency-modulated continuous-waveform (FMCW)-based 128 channel (8 transmitters (T x ), 16 receivers (R x )) MIMO radar sensor. The 77GHz synthetic radar returns from full scale traffic scenes are obtained using a high-fidelity physics, shooting and bouncing ray electromagnetics solver. A fast Fourier transform (FFT) based signal processing scheme is used across slow-time (chirp) and space (channel) to obtain range-Doppler and DoA maps, respectively. Detection and angular separation performance comparisons of 16, 64 and 128 channel MIMO radar sensors are made for two complex driving scenarios.

Patch and monopole antennas in linear coprime arrays for direction of arrival estimation using compressed sensing

Original work on direction of arrival (DOA) estimation relied on uniform linear arrays (ULAs) of antennas. Most of the work focused on improving the algorithms and the configuration of the antenna array and overlooked the effects of practical antennas on the algorithm performance. Very limited work studied DOA estimation within the physical limitations of handheld devices. In this work, we introduce three nonuniform linear coprime arrays based on patch and monopole antenna elements operating in 2.1 and 5.8 GHz bands and assess their behaviour in DOA estimation. The complex radiation patterns of the arrays were incorporated in the DOA estimation algorithm using compressed sensing (CS). Estimation accuracy is quantified by the root mean square error (RMSE) and the results are compared with those obtained by using isotropic antennas, showing that physical antennas can introduce up to 8° of error. Simulations were also carried out using the multiple signal classification (MUSIC) algorithm to demonstrate the advantage of CS in coprime arrays. The MUSIC algorithm failed to detect all sources even at maximum SNR. The impact of reducing the fundamental inter-element spacing in coprime arrays below 0.5 λ to achieve smaller array sizes is investigated as well.

Two-Dimensional DOA Estimation via Shifted Sparse Arrays with Higher Degrees of Freedom

Sparse antenna arrays provide larger virtual arrays to estimate the direction of arrivals (DOAs) of more sources than the number of physical antennas in the array. While the degrees of freedom (DOF) can be increased by the special structure of the antenna array, a shift in the antenna positions can generate new lags in the difference co-array; hence, more sources can be resolved. In this paper, we propose shifted sparse array structures composed of two overlapping arrays shifted by one lag. It is shown that the shifting property fills the holes in the co-array, which yields larger virtual arrays. We derive stationary and moving array models where overlapping sparse arrays can be realized. The proposed shifting property is applied to coprime, nested and sparse linear arrays, and we show that the proposed technique guaranteed to increase the DOF. Using the proposed sparse array structures, we also propose a 2-D DOA estimation algorithm by utilizing the cross-covariance matrix of an L-shaped sparse array. The performance of the proposed approach is evaluated through numerical simulations, and we show that it can resolve more sources than the conventional sparse arrays with the same number of physical antennas, providing less computational complexity.

Experimental Assessment of the Coarray Concept for DoA Estimation in Wireless Communications

The direction of arrival (DoA) estimation performance of three different coarray structures, namely, the nested array, the coprime sampling array, and the sparse ruler array are presented and compared. The coarray concept makes it possible to detect the DoAs of much more sources than the number of physical antennas. Crucial is that for the first time, these coarrays are investigated based on real measurements conducted on a demonstrator platform. Based on the results obtained, the conclusion is clear. The MUSIC algorithm-based coarray concept with spatial smoothing is not suitable for DoA estimation in practical circumstances due to the unavoidable multipath phenomenon.

Fast DOA Estimation Algorithms for Sparse Uniform Linear Array With Multiple Integer Frequencies

The sparse uniform linear array (SULA) with larger array aperture is adopted to improve the accuracy of direction of arrival (DOA) estimation with a limited number of physical antennas. In the case of single working frequency configuration, spatial aliasing problem occurs due to the spatial under-sampling. However, with a sufficient anti-aliasing condition for multiple frequencies, the unique DOA estimations can be obtained without ambiguity by using multiple integer frequencies. The multiple equivalent array structures of the multiple integer frequencies are analyzed. To perform DOA estimation, in the first part of the paper, a pair of fast DOA estimation methods are proposed. Based on the fact that a real DOA and its ambiguous positions are periodic distributed in the sine domain, the two proposed methods are applied to each equivalent array separately to obtain the real DOA positions as well as their replica positions. Then, an effective matching algorithm is proposed to pick out the real DOAs from the ambiguous ones. The first algorithm is a partial spectral search-based algorithm, and the second algorithm is a search-free-based method. These two algorithms are referred to as matching partial spectral search-based algorithm (matching PPS) and matching root-multiple signal classification algorithm (matching root-MUSIC), respectively. Our third proposed algorithm is a combined root-MUSIC which is applied to the multiple equivalent arrays by taking them as sub-arrays of a common filled ULA. The combined root-MUSIC algorithm utilizes the MUSIC null-spectrum functions of all equivalent arrays to form a new polynomial, and the DOA estimations can be obtained efficiently without any spatial ambiguity by applying polynomial rooting to the new polynomial. Simulations are provided to verify the validity of the proposed algorithms.

Construction and Analysis of Quaternion MIMO-OFDM Communications Systems

Wireless communications systems with progressively higher spectral efficiency have been investigated in past decades. A promising area of research is the use of hypercomplex algebras, notably, the use of the quaternion algebra. This paper considers the construction of multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) using the algebra of quaternions. Several construction techniques for quaternion orthogonal code designs have been proposed in recent years, which offer the possibility to explore diversities in variate domains, such as space, time, frequency, and polarization, in addition to combinations thereof. This paper presents a formulation for quaternion MIMO-OFDM in matrix form as an extension of the classical formulation that uses complex variables. Quaternions allow elegant representation of pairs of radiant elements in physical antennas configured for cross-polarized propagation. Several simulations validate the proposed method in diverse scenarios for wireless communications, in which combined diversities have been exploited.

3D nested distributed massive MIMO: Modeling and performance analysis

The Large Scale Multiple-input-multiple-output (MIMO) system, also called Massive MIMO in past researches, are considering the azimuth angle only. However, in a 3D distributed antenna system, the elevation angle cannot be ignored. Nested array as a two dimensional arrays was firstly proposed to perform array processing with increased degree of freedom, using less number of sensors at the same time. This paper introduces a novel 3D MIMO antenna deployment based on nested co-array. As the difference co-arrays are invariance, in the 3D nested distributed MIMO system, we are able to calculate the covariance matrix of channels. Based on this inference, we model a 3D nested distributed MIMO system and analyze its performance with achievable sum rate. By applying the nested deployment, our proposed method could achieve a Massive MIMO with less number of physical antennas. Numerical results also provided to support our model.

Extended low‐density parity‐check codes for feedback‐based cooperative diversity schemes

Cooperative diversity or user cooperation achieves the diversity gain without adding physical antennas to the users or mobile stations. The users work in a cooperative fashion by using their single antennas to create a virtual transmit diversity, called relay diversity or cooperative diversity. The diversity gain achieved by cooperative diversity can be further improved using error correction codes. Low-density parity-check (LDPC) codes are linear block codes with good error correction capabilities. The authors present a novel approach using extended LDPC codes to increase the diversity gain in cooperative diversity. The authors also compare the extended LDPC codes with the punctured LDPC codes in a cooperative diversity and show that there is a performance–complexity tradeoff between the punctured and the extended LDPC codes in the cooperative diversity. Furthermore, the authors will propose two feedback-based protocols for cooperative diversity and compare their throughput with non-feedback-based cooperative diversity using extended LDPC codes.

AOD estimation in WSN localization system with synthetic aperture technique

Angel of departure (AOD) based distributed localization scheme in wireless sensor networks allows the single antenna sensor node to estimate its own AOD information by an equivalent antenna array for further position calculation. However, the condition that the number of antennas at the multi-antenna agent/anchor node should be larger than the number of multipath signal components (MPCs) constrains its actual application. In this paper, we provide a more practical approach to achieve AOD information estimation under multipath environment. Given that the sensor node can not identify the line of sight (LOS) signal component due to the insufficient degree of freedom, which is determined by the above limiting condition, we introduce a synthetic aperture technique with the aid of a fast moving multi-antenna agent/anchor node. This operation greatly enlarges the degree of freedom of the equivalent antenna array constructed at sensor node end but without requiring other extra physical antennas equipped at agent/anchor node or sensor node end, which means that it relaxes the limiting condition. Therefore, the AOD information of LOS signal component can be estimated and extracted successfully in complex multipath environment. Theoretical analysis proves the effectiveness of our proposed synthetic aperture technique and numerical simulations show great performance improvement.

MIMO 레이더에서 송수신 안테나 분배에 의한 최적 성능에 관한 연구

본 논문에서 우리는 등간격 선형 어레이 (ULA : Uniform Linear Array) MIMO 레이더 시스템에 ESPRIT 알고리즘을 적용하여 전송각과 도래각을 추정하는 방법을 고려한다. 각 추정 성능을 높이기 위한 방안으로 물리적인 안테나 개수를 증가시키는 방법과 정합필터링 후의 스냅샷 수를 증가시키는 방법이 있지만 이러한 방법에는 복잡도 등의 다양한 제약이 따른다. 이에 본 논문에서는 단순히 전송, 수신 안테나 수를 적절히 분배함으로서 성능을 향상시키는 방법을 제안하고자 한다. 특히, 우리는 수신 안테나의 수가 송신 안테나 수의 약 두배가 되었을 때 최적의 성능이 얻어짐을 보인다. In this paper, we study the method of estimating direction of departure(DOD) and direction of arrival(DOA) using estimation of signal parameters via rotational invariant techniques (ESPRIT) in uniform linear array MIMO radar system. While it is possible to improve the resolution by increasing the numbers of physical antennas and snapshots after matched filtering, such methods generally give rise to increase in complexity. In this paper, we propose to improve the resolution by optimally allocating the number of transmit and receive antennas. In particular, we show that the performance is optimized when the number of the receive antennas is approximately twice that of transmit antennas.

SNR Performance Analysis of Reconfigurable Antennas

Reconfigurable antenna arrays offer advantages over traditional antenna selection in terms of requiring fewer physical antennas and the use of fixed antenna feeds. Hence, in this paper we analyze the signal to noise ratio (SNR) improvement offered by reconfigurable antennas and compare it to traditional selection. Both the distribution and the mean value of the link gains in a reconfigurable system are derived and used to gain insight into system performance, both for SNR gain and outage. Results demonstrate that for systems with up to four antennas and two radiation states, reconfiguration can provide at least 76% of the improvements offered by selection.

Space Station based tethered interferometer for natural disaster monitoring

A synthetic aperture radar interferometer based on two vertically spaced physical antennas carried along parallel paths by the Space Station and by a small tethered subsatellite is presented. This remote sensing system is aimed at producing and updating topographic maps. In particular, it offers geometric, radiometric, and temporal resolutions adequate for natural-disaster monitoring. The system performance is identified by means of a computer simulation, taking account of the tethered platform dynamics and of the Space Station orbital decay. Numerical results show the capability of observing any point of the Earth surface in the range of latitudes ±51.6 deg with a repetitivity of about 2 days, by using range steering of the antenna beams (15-45 deg). Then, the attitude pointing accuracy requirements are derived by evaluating the signal-to-noise ratio and the swath overlap decrease due to the antenna misalignment (yaw 0.15 deg, pitch 0.10 deg, roll 0.20 deg).

Comments on "Nondispersive waves: interpretation and causality", by P.T.M. Hillion [with reply

Heyman and Felsen comment on a paper by Hillion (IEEE Trans. Antennas Propag., vol.AP-40, p.1031-5, 1992). Hillion gives a reply. The articles discuss nondiffracting wave objects and how they can be excited by physical aperture antennas.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Attitude dynamics and control of a vertical interferometric radar tethered altimeter

This paper investigates the attitude dynamics and control of a vertical interferometric synthetic aperture radar tethered altimeter: a system based on two space platforms of comparable mass connected by 1-km tether. Two vertically spaced physical antennas on these platforms supply the terrain height measurement data by making use of radar interferometry. Since the height accuracy is strongly affected by the combined dynamics of the two platforms, this paper will focus on the analysis and control of high-frequency attitude oscillations. The results show that the proposed control system can limit the attitude angle differences and rates to 10 ~ 3 and 10 ~ deg/s, respectively, as required by the proposed application.