Calibration and Direction-of-Arrival Estimation of Millimeter-Wave Radars: A Practical Introduction

Vasanelli, Claudia; Roos, Fabian; Dürr, André; Schlichenmaier, Johannes; Hügler, Philipp; Meinecke, Benedikt; Steiner, Maximilian; Waldschmidt, Christian

doi:10.1109/map.2020.2988528

Cited by 58 publications

(46 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In traditional radar signal processing using digital beamforming on the receiver side, the range-Doppler matrices of each virtual channel are noncoherently accumulated into a single range-Doppler matrix [16], [23]. The resulting matrix contains information from all channels and provides a basis for the extraction of potential targets.…”

Section: A Description Of the Range-angle Coupling Effectmentioning

confidence: 99%

“…To demonstrate the improvement in DoA estimation, the measurement results are compared with state-of-the-art signal processing with the entire array (upper row in Fig. 7) without a frequency and phase correction [16], [30], [31].…”

Section: B Influence Of the Range-angle Coupling Effectmentioning

confidence: 99%

“…Since phased arrays or mechanical scanning antennas are expensive, the direction-of-arrival (DoA) is determined by digital delay-and-sum beamforming on the receiver side in a lot of low-cost applications. Typically, the DoA of the target is estimated after a previous range-Doppler processing and subsequent target extraction [16]. For typical multiple-input multiple-output (MIMO) radars using conventional aperture sizes or modulation bandwidths, the difference in path length of the incident wave at the receive antennas does not noticeably exceed the range resolution of the radar, see [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Range-Angle Coupling and Near-Field Effects of Very Large Arrays in mm-Wave Imaging Radars

Dürr¹,

Schneele²,

Schwarz³

et al. 2021

IEEE Trans. Microwave Theory Techn.

Self Cite

View full text Add to dashboard Cite

In order to improve the resolution of imaging radars, electrically large arrays and a high absolute modulation bandwidth are needed. For radar systems with simultaneously high range resolution and very large aperture, the difference in path length at the receiving antennas is a multiple of the range resolution of the radar, in particular for off-boresight angles of the incident wave. Therefore, the radar response of a target measured at the different receiving antennas is distributed over a large number of range cells. This behavior depends on the unknown incident angle of the wave and is, thus, denoted as range-angle coupling. Furthermore, the far-field (FF) condition is no longer fulfilled in short-range applications. Applying conventional signal processing and radar calibration techniques leads to a significant reduction of the resolution capabilities of the array. In this article, the key aspects of radar imaging are discussed when radars with both large aperture size and high absolute bandwidth are employed in short-range applications. Based on an initial mathematical formulation of the physical effects, a correction method and an efficient signal processing chain are proposed, which compensate for errors that occur with conventional beamforming techniques. It is shown by measurements that with an appropriate error correction an improvement of the angular resolution up to a factor of 2.5 is achieved, resulting in an angular resolution below 0.4 • with an overall aperture size of nearly 200 λ 0 .

show abstract

Section: A Description Of the Range-angle Coupling Effectmentioning

confidence: 99%

Section: B Influence Of the Range-angle Coupling Effectmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Range-Angle Coupling and Near-Field Effects of Very Large Arrays in mm-Wave Imaging Radars

Dürr¹,

Schneele²,

Schwarz³

et al. 2021

IEEE Trans. Microwave Theory Techn.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the determination of the absolute position of a calibration target relative to the sensor puts high demands on the reference system. Therefore, common approaches work in the far-field of the array and hence only require the knowledge of the target's angle relative to the sensor [12], [13], [15]. This angle can be acquired approximately by rotating the radar around the antenna center.…”

Section: Introductionmentioning

confidence: 99%

Antenna Array Calibration Using a Sparse Scene

Geiß

Sippel

Hehn

et al. 2021

IEEE Open J. Antennas Propag.

View full text Add to dashboard Cite

In radar systems, antenna arrays acquire direction-dependent information to localize targets or create images of the environment. However, because of unknown complex amplitudes per channel and mutual coupling, a calibration is necessary for good performance. Common calibration approaches measure to targets under known angles in a multipath-free far-field environment, which often can only be provided by anechoic chambers. Therefore, this process is not suitable for low-cost and frequent calibration. To overcome these limitations, this paper proposes a novel calibration approach using an unknown but sparse target scene. Multiple measurements at known relative positions of the radar are combined to a synthetic aperture. Then, the full mutual coupling matrix is estimated simultaneously with the unknown target scene. The method requires neither target position information, far-field conditions, nor an anechoic chamber because multipath propagation can be suppressed easily for targets located in the near-field. The proposed calibration approach is validated by measurements of a commercial 77 GHz radar. The performance is evaluated by comparing the achieved image quality using the calibration results of this work and the radar's ex-factory calibration data. The proposed novel calibration procedure improves the image quality, while considerably lowering the demands on the calibration measurements and environment.

show abstract

“…The focus of this paper is on acoustic sound source localization, where sensors are microphones [2]. However, we note that DOA estimation is also widely applied in radar [3] and sonar [4] technologies.…”

Section: Introductionmentioning

confidence: 99%

Refinement of Direction of Arrival Estimators by Majorization-Minimization Optimization on the Array Manifold

Scheibler

Togami

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

We propose a generalized formulation of direction of arrival estimation that includes many existing methods such as steered response power, subspace, coherent and incoherent, as well as speech sparsity-based methods. Unlike most conventional methods that rely exclusively on grid search, we introduce a continuous optimization algorithm to refine DOA estimates beyond the resolution of the initial grid. The algorithm is derived from the majorizationminimization (MM) technique. We derive two surrogate functions, one quadratic and one linear. Both lead to efficient iterative algorithms that do not require hyperparameters, such as step size, and ensure that the DOA estimates never leave the array manifold, without the need for a projection step. In numerical experiments, we show that the accuracy after a few iterations of the MM algorithm nearly removes dependency on the resolution of the initial grid used. We find that the quadratic surrogate function leads to very fast convergence, but the simplicity of the linear algorithm is very attractive, and the performance gap small.

show abstract

Calibration and Direction-of-Arrival Estimation of Millimeter-Wave Radars: A Practical Introduction

Cited by 58 publications

References 25 publications

Range-Angle Coupling and Near-Field Effects of Very Large Arrays in mm-Wave Imaging Radars

Range-Angle Coupling and Near-Field Effects of Very Large Arrays in mm-Wave Imaging Radars

Antenna Array Calibration Using a Sparse Scene

Refinement of Direction of Arrival Estimators by Majorization-Minimization Optimization on the Array Manifold

Contact Info

Product

Resources

About