Enhanced Velocity Estimation Based on Joint Doppler Frequency and Range Rate Measurements

Lim, Sohee; Jung, Jaehoon; Kim, Jihye; Kim, Seong-Cheol; Choi, Jeongsik

doi:10.1109/icufn55119.2022.9829630

Cited by 4 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the proposed framework therein is only limited to the estimation of velocities lower than a certain maximum velocity and the spectra of signals of targets with velocities higher than the velocity corresponding to the Nyquist rate are still aliased, and hence cannot be accurately estimated. To address this issue, Sohee et al in [31] proposed a method for velocity estimation while simultaneously resolving the velocity ambiguity in a frequency-modulated continuous wave (FMCW) radar system. The authors of [32] proposed a tensor generalized weighted linear predictor (TGWLP) for a frequency diverse array (FDA) MIMO radar toward parallel estimation of radar parameters.…”

Section: A Review Of Existing Workmentioning

confidence: 99%

See 1 more Smart Citation

Sparse Parameter Estimation and Imaging in mmWave MIMO Radar Systems With Multiple Stationary and Mobile Targets

et al. 2022

View full text Add to dashboard Cite

This work conceives novel target detection and parameter estimation schemes in millimeterwave (mmWave) multiple-input multiple-output (MIMO) radar (mMR) systems for both stationary and mobile targets/radar platform. Initially, the orthogonal matching pursuit (OMP)-based mmR (OmMR) algorithm is proposed for stationary targets to estimate their radar cross-section (RCS) coefficients, angle, range locations together with the number of targets. Next, mMR systems with mobile targets and platform are considered, followed by development of the simultaneous OMP (SOMP)-based mMR (SmMR) algorithm for RCS, angle/range estimation together with their Doppler velocities. The proposed algorithms lead to a significant improvement in performance since they exploit the inherent sparsity of the mMR scattering scene in contrast to the conventional schemes. Two-dimensional (2D) mMR imaging procedures are also presented for both scenarios in the angle, range, and Doppler dimensions. Analytical expressions are derived for the Cramér-Rao bounds (CRBs) for the mean-squared error (MSE) of joint estimation of the RCS coefficients and Doppler velocities. Simulation results demonstrate that proposed schemes perform well even in low signal-to-noise ratio (SNR) scenarios with a few snapshots of the scattering environment and yield improved performance in comparison to existing sparse as well as non-sparse schemes.

show abstract

Section: A Review Of Existing Workmentioning

confidence: 99%

“…Substituting the various quantities derived above, one can readily obtain the Fisher Information matrices which in turn yield the CRBs in ( 30), (31). For the case of a stationary mMR system, the unknown parameter vector Θ = γeff ∈ R 2QR×1 .…”

Section: Cramér-rao Boundsmentioning

confidence: 99%