# One-Bit Radar Processing with Time-Varying Sampling Thresholds

arXiv: https://arxiv.org/abs/1911.10170 · HTML: https://mlsanity.com/paper/1911.10170/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Nov 2019.

## Built on by (most cited first, 7 of 7)

- [LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receivers](https://mlsanity.com/paper/2102.02993/) (2021)
- [Hardware Implementation of Task-based Quantization in Multi-user Signal Recovery](https://mlsanity.com/paper/2301.11640/) (2023)
- [Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information](https://mlsanity.com/paper/2302.10450/) (2023)
- [One-bit Compressed Sensing using Generative Models](https://mlsanity.com/paper/2502.12762/) (2025)
- [Model-Based Learning for DOA Estimation with One-Bit Single-Snapshot Sparse Arrays](https://mlsanity.com/paper/2502.17473/) (2025)
- [Weak target detection with multi-bit quantization in colocated MIMO radar](https://mlsanity.com/paper/2106.00612/) (2021)
- [Deep Probabilistic Unfolding for Quantized Compressive Sensing](https://mlsanity.com/paper/2605.11475/) (2026)

## Abstract (arXiv)

Target parameter estimation in active sensing, and particularly radar signal processing, is a long-standing problem that has been studied extensively. In this paper, we propose a novel approach for target parameter estimation in cases where one-bit analog-to-digital-converters (ADCs), also known as signal comparators with time-varying thresholds, are employed to sample the received radar signal instead of high-resolution ADCs. The considered problem has potential applications in the design of inexpensive radar and sensing devices in civilian applications, and can likely pave the way for future radar systems employing low-resolution ADCs for faster sampling and high-resolution target determination. We formulate the target estimation as a multivariate weighted-least-squares optimization problem that can be solved in a cyclic manner. Numerical results are provided to exhibit the effectiveness of the proposed algorithms.