Parameter estimation for MIMO channel sounding data aims at accurately describing channel measurements with physically realistic and interpretable parameters. The performance of model based approaches, e.g. maximum likelihood, is determined by the accuracy of the imposed signal model. For channel sounding data it has turned out to be beneficial to use two distinct concepts for the description of the propagation process. The specular components account for the dominant propagation paths of plane waves, whereas diffuse components model the weaker but more diverse propagation processes by means of a colored noise process. In order to improve the accuracy of the model for the diffuse components we propose a simple but still flexible parametric covariance model that allows to account for a smooth power angle profile that describes the correlation in the spatial domain. Moreover, the model for the deterministic part of the signal is usually contaminated by calibration errors, which in turn deteriorate the reliability of the specular path estimates. This is most prominently visible by the estimation of so-called ghost paths. To mitigate this we introduce a new model order selection scheme based on the so-called misspecified Cramèr Rao bound which accounts for the unavoidable modeling errors. Additionally, to avoid the fitting of ghost paths caused by the faulty modeling of strong specular components we locally decrease the estimated SNR in time domain around already estimated ones. Further, as these changes to the signal model require more computational resources compared to existing algorithms, we also showcase how necessary quantities like likelihoods, score functions and fisher information matrices can still be computed efficiently. We implement our proposed extensions within the RIMAX framework. We also showcase that they improve the reliability of the produced estimates compared to plain vanilla RIMAX on real measurement data.

In this publication, we analyze how the performance of propagation parameter estimation for THz channel sounding can be improved by the power spectrum design of a multicarrier waveform. To this end, we discuss the Fisher information of the propagation parameters and the corresponding deterministic Cramèr-Rao lower bound (CRB) as well as their relation to the carrier powers of the excitation signal. We use these quantities to design waveforms that improve range estimation. In practice, optimizing the power spectrum requires prior knowledge of the propagation scenario which is usually not available. Hence, we propose two solutions which we compare numerically to the classical approach of equal power distribution. The numerical evaluation shows that an optimized power distribution can improve the CRB comparable up to a 4 dB gain in SNR depending on whether knowledge about the scenario can be acquired in advance with an additional measurement. © 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

This publication proposes a parametric data model and a gradient-based maximum likelihood estimator suitable for the description of delay-dispersive responses of multiple dynamic UWB-radar targets. The target responses are estimated jointly with the global target parameters range and velocity. The large relative bandwidth of UWB has consequences for model-based parameter estimation. On the one hand, the Doppler effect leads to a dispersive response in the Doppler spectrum and to a coupling of the target parameters which both need to be considered during modeling and estimation. On the other hand, the shape of an extended target results in a dispersive response in range which can be resolved by the radar resolution. We consider this extended response as a parameter of interest, e.g., for the purpose of target recognition. Hence, we propose an efficient description and estimation of it by an FIR structure only imposing a restriction on the target’s dispersiveness in range. We evaluate the approach on simulations, compare it to state of the art solutions and provide a validation on measurement data. © 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works .

Multidimensional channel sounding measures the geometrical structure of mobile radio propagation. The parameters of a multipath data model in terms of directions, time-of-flight and Doppler shift are estimated from observations in frequency, time and space. A maximum likelihood estimation framework allows joint high-resolution in all dimensions. The prerequisite for this is an appropriate parametric data model that represents the multipath propagation correctly. At the same time, a device data model is necessary that typically results from calibration measurements. The used model should be as simple as possible since its structure has a considerable effect on the estimation effort. For instance, the inherent effort in parameter search is reduced if the influence of the parameters is kept orthogonal. Therefore, the data model is characterized by several approximations. The most important is the “narrowband assumption” which assumes a low relative bandwidth and also avoids considering any frequency response in magnitude and phase. We extend the well-known multidimensional \gls{rimax} parameter estimation framework by including proper frequency responses. The advantage reveals most clearly with high bandwidth in the mmWave and sub-THz range. It allows for a more realistic modeling of antenna arrays. It breaks with the usual narrowband model and allows a better modeling of mutual coupling and time delay effects. If the interacting object extends over several delay bins (hence an extended target in radar terminology) we propose a model that assigns a short delay spread, respectively a frequency response to the propagation path that associates itto the respective object. We verify the validity of the device model by numerical experiments on simulated and measured antenna data and compare it to a state-of-the-art method. Additionally, we use synthetic data based on raytracing results and measurements both ranging from \SI{27}{\giga\hertz} up to \SI{33}{\giga\hertz} with known ground truth information and show that the proposed estimator not based on the narrowband assumption delivers better performance for higher relative bandwidths than the conventional \gls{rimax} implementation.