Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing

Abstract

There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth. One of the most promising solutions is the use of compressed sensing (CS) algorithms, which assume only the sparseness of the target distribution but can achieve super-resolution. To preserve the reconstruction accuracy of CS under highly correlated and noisy conditions, we introduce a random resampling approach to process the received signal and thus reduce the coherent index, where the frequency-domain-based CS algorithm is used as noise reduction preprocessing. Numerical simulations demonstrate that our proposed method can achieve super-resolution TOA estimation performance not possible with conventional CS methods.

Three‐dimensional Doppler‐associated radar imaging method based on bi‐directional data processing

“…It should be also noted that the literature [31] demonstrated that a simple Doppler‐range separation scheme using the STFT and matched filtering could not separate the actual range‐Doppler profile, due to RW problem and lower temporal and velocity resolutions, in the same model assumed in this simulation. Thus, in this study, the super‐resolution CS filter [30] is applied for the range extraction filter, this is because a desired range profile is expressed as an aggregation of Dirac's Delta function, and such profile generally has a sparse feature. Furthermore, while the actual Doppler velocities of lower arms or legs exceed the unambiguous velocity range ( 0.75 m/s), the WKD‐based method provided accurate Doppler velocity over the above range, i.e., a distinguished advantage of the WKD over the Fourier transform‐based method.…”

“…Furthermore, at lower pulse repetition frequencies, the reflection echoes slide to another range gate at a different pulse hit, which is known as the range walk (RW) effect. For range resolution, certain super‐resolution time‐of‐flight (TOF) estimations, such as multiple signal classification (commonly known as MUSIC), Capon, and compressed sensing (CS), have been proposed [30]. However, since these filters have very impulsive waveforms (narrower pulse width), they have considerably lower carrier frequencies, the RW problem could be more severe.…”

Doubling the Accuracy of Indoor Positioning: Frequency Diversity

“…Several super-resolution methods are used, such as MUSIC, ESPRIT, and pencil matrix [19][20][21][22][23][24][25][26]. These are based on specific assumptions about the transfer function of the communication channel.…”