Antenna Array Calibration Using a Sparse Scene

Abstract

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.

The Impact of Antenna Array Calibration Errors on MIMO and Multi-Channel Synthetic Aperture Radar Imaging

“…All relations found in this work are also valid if only a few measurements are performed or the far-field condition is not fully met, as will be demonstrated by the simulations within this section and the measurements in Section VII. Third, the transmit signal S t ( f ) is assumed to have a limited bandwidth such that (13) and, thus, ( 16) holds [25], which should be valid for most radar systems.…”

“…Thereby, we account for the fact, that the coupling amplitude is mainly given by the antenna distance, and, therefore, can be assumed to be approximately known and symmetric [24]. It was discussed in [25] that the assumption of constant coupling is valid in typical radar systems with limited bandwidth such as FMCW radar. In special cases, where the above assumptions are not justified, the following derivation of a worst-case SDR may still be useful to provide a rough estimate of the expected image distortion caused by mutual coupling.…”

“…This simplifies online-calibration in unknown environments drastically. Offline calibration approaches, as in [25], [26], already exploit the sparsity of an unknown target scene to perform simultaneous calibration and imaging. By exploiting the formation of ghost targets in a proper measurement setup, the known separation of signal and error power may significantly lower the requirements on the imaging part of such a calibration.…”

“…Calibration procedures usually require measurements to targets at known positions in a multipathfree far-field environment, such as an anechoic chamber [22], [23], [24]. Using elaborated approaches, as in [25], [26], allows to reduce the high requirements on the calibration setup. Nevertheless, radar sensors, especially in the automotive sector, typically suffer from some residual calibration error because no sufficiently frequent recalibration is performed to maintain high imaging quality [27].…”

“…Then, radar images were reconstructed via backprojection [31]. First, the calibration data found via the offline calibration proposed in [25] was used and second, additional phase errors of ±20 • were added to the individual channels during the reconstruction. The resulting images are shown in Figure 1(c) and 1(d), respectively.…”