In this work, a 24-GHz frequency-modulated continuous-wave (FMCW) radar system with two sectoral horn antennas and one transmitting lens antenna for long-range drone detection is presented. The present work demonstrates the detection of a quadcopter-type drone using the implemented radar system up to a distance of 1 km. Moreover, a 3D subspace-based algorithm is proposed for the joint range-azimuth-Doppler estimation of long-range drone detection. The effectiveness of the long-range drone detection is verified with the implemented radar system through a variety of experiments in outdoor environments. This is the first such demonstration for long-range drone detection with a 24-GHz FMCW radar.

In this paper, a modified 3D multiple signal classification (MUSIC) algorithm is proposed for joint estimation of range, azimuth, and elevation angles of K-band radar with a small 2 × 2 horn antenna array. Three channels of the 2 × 2 horn antenna array are utilized as receiving channels, and the other one is a transmitting antenna. The proposed modified 3D MUSIC is designed to make use of a stacked autocorrelation matrix, whose element matrices are related to each other in the spatial domain. An augmented 2D steering vector based on the stacked autocorrelation matrix is proposed for the modified 3D MUSIC, instead of the conventional 3D steering vector. The effectiveness of the proposed modified 3D MUSIC is verified through implementation with a K-band frequency-modulated continuous-wave (FMCW) radar with the 2 × 2 horn antenna array through a variety of experiments in a chamber.

This article deals with the development of a dual channel S-Band frequency-modulated continuous wave (FMCW) system for a through-the-wall imaging (TWRI) system. Most existing TWRI systems using FMCW were developed for synthetic aperture radar (SAR) which has many drawbacks such as the need for several antenna elements and movement of the system. Our implemented TWRI system comprises a transmitting antenna and two receiving antennas, resulting in a significant reduction of the number of antenna elements. Moreover, a proposed algorithm for range-angle-Doppler 3D estimation based on a 3D shift invariant structure is utilized in our implemented dual channel S-band FMCW TWRI system. Indoor and outdoor experiments were conducted to image the scene beyond a wall for water targets and person targets, respectively. The experimental results demonstrate that high-quality imaging can be achieved under both experimental scenarios.

In this paper, a three-dimensional (3D)-subspace-based azimuth angle, elevation angle, and range estimation method with auto-pairing is proposed for frequency-modulated continuous waveform (FMCW) radar with an L-shaped array. The proposed method is designed to exploit the 3D shift-invariant structure of the stacked Hankel snapshot matrix for auto-paired azimuth angle, elevation angle, and range estimation. The effectiveness of the proposed method is verified through a variety of experiments conducted in a chamber. For the realization of the proposed method, K-band FMCW radar is implemented with an L-shaped antenna.

We propose a novel time delay estimation algorithm using a training and data sequence composed of chirp signals for a ranging system with frequency offset. This training and data sequence can be used for SNR enhancement using the proposed denoising method. Then, a subspace-based algorithm, ESPRIT, is applied to estimate the time delay of the first arrival path. We analyze the estimation performance of ESPRIT based on the proposed denoising method and verify it through Monte-carlo simulations in AWGN and a multi-path channel.

In this letter, an effective pre-filtering method is proposed with Propagator for accurate time-of-arrival (TOA)-based range estimations. For TOA estimation using subspace fitting techniques such as Propagator, the received signals must be transformed into sinusoid. After the transformation, the bandwidth of the sinusoids is no longer dependent on the transmitted baseband signal but on channel parameters. By applying the pre-filtering method with the sinusoids, we can remove the outband noise of the sinusoids and this leads to more accurate TOA estimation due to the noise reduction. The effectiveness of the proposed pre-filtering method was analyzed and verified through Monte-carlo simulations in additive white Gaussian noise (AWGN) and multipath channels.