Without any relative moves or beam scanning, the novel Orbital-Angular-Momentum- (OAM-) based radar targets detection technique using uniform concentric circular arrays (UCCAs) shows the azimuthal estimation ability, which provides new perspective for radar system design. However, the main estimation method, that is, Fast Fourier Transform (FFT), under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC) algorithm to improve the resolution for detecting targets within the main lobes. The spatial smoothing technique is proposed to tackle the coherent problem brought by the proposed model. Analytical study and simulation demonstrate the superresolution estimation capacity the MUSIC algorithm can achieve for detecting targets within the main lobes. The performance of the MUSIC algorithm to detect targets not illuminated by the main lobes is further evaluated. Despite the fact that MUSIC algorithm loses the resolution advantage under this case, its estimation is more robust than that of the FFT method. Overall, the proposed MUSIC algorithm for the OAM-based radar system demonstrates the superresolution ability for detecting targets within the main lobes and good robustness for targets out of the main lobes.
Orbital Angular Momentum (OAM) has been widely studied in the optic regime regarding imaging, microscopic particle, and communication [
Previous works about radio OAM mainly focused on communication systems consisting of two subfields, namely, performance analysis and design of antennas to generate twisted beams [
Target illuminated by (a) the traditional beam with planar wave and (b) the twisted OAM beam with helical wavefront.
Based on the scenario in [
The MIMO and MISO schemes of OAM-based radar techniques were investigated in [
Uniform concentric circular arrays.
The normalized received echo signal using the UCCAs under the MIMO scheme can be written as follows:
Despite the fact that detection technique using the UCCAs could enhance the echo signal for targets within main lobes, the low-resolution estimation method FFT limits its application for detecting targets with narrow azimuth angle gaps. For targets within main lobes, this section rebuilds the model to achieve the superresolution by using the MUSIC algorithm. It is assumed that the prior information of target number
According to (
For presenting Gaussian noise, the covariance matrix of the echo signals under different OAM modes can be acquired by
According to the smoothing theory [
Front-spatial smoothing in
The whole procedure of the spatial smoothing MUSIC algorithm to estimate the azimuth angles is listed as follows: Obtain Gain Make engine value decomposition of Calculate the azimuth spectrum where
Similar conclusions can be retained for MISO scheme, but with several differences as follows: To avoid aliasing, the minimum sample rate of MISO scheme is half that of MIMO scheme. The resolution ability of MIMO scheme is double that of MISO scheme, with The searching steering vector is
The targets detection within the designed main lobes is described in Section
According to (
According to signal processing theory, the multiplication relation in
Azimuth profile of PSF using the same UCCA configuration with main lobes aimed at
Azimuth profile of PSF of the same target with
Simulation is presented to compare performances of the existing FFT method and the proposed MUSIC algorithm. Figure
Azimuth angle estimation spectrum under MIMO scheme: (a) and (b); MISO scheme: (c) and (d). (a) and (c) use the FFT method, while (b) and (d) utilize the MUSIC algorithm. Two targets at
Resolution angle against SNR using (a) FFT and (b) MUSIC (
Using UCCA configuration as Figure
Azimuthal estimation for targets out of main lobes using (a) FFT and (b) MUSIC. Directions of two targets are
For the Orbital-Angular-Momentum- (OAM-) based radar system using uniform concentric circular arrays (UCCAs), this paper addressed the multiple signal classification (MUSIC) algorithm to improve the target detection performance. In comparison with the traditional FFT method, the proposed MUSIC algorithm achieved the superresolution for detecting the targets within the main lobes and good robustness for detecting the targets out of the main lobes. Benefiting from the high-resolution ability, the same performance as the FFT was achieved by lower number of the OAM modes using the MUSIC algorithm and thus reduced the design complexity and cost of the hardware. The proposed model was built with the ideal propagation loss; however the gain loss for each OAM mode of the real system could be complex and would introduce the deviation. Further work could be focused on the calibration technique with measured propagation loss difference of each OAM mode to further reduce the estimation error.
The authors declare that they have no competing interests.