Multiplexing Radar Research Articles

Clear-Air Bragg Scattering Observed above the Convective Boundary Layer in the Morning

Reflected waves have been frequently observed via weather radar, even during sunny, cloudless days. Additionally, it is recognized that turbulence and biological scatterers can also dominate the scattering process. In previous studies, echo returns of turbulence from clear-air Bragg scattering (CABS) have been used to detect the height of the convective boundary layer (CBL). However, in a dual-frequency antenna multiplexing radar system, through which the dual-wavelength ratio (DWR) identifies the CABS clearly, CABS can be unexpectedly observed not only at the edge of the CBL but also above the CBL, highlighting the need for an expanded set of causes of clear-air echoes. It was further identified that the negative second derivative of horizontal wind speed, which is measured by a coherent Doppler Lidar, is consistent with the variation of the CABS layers’ height above the CBL. These results emphasize the presence of physical processes leading to turbulence in the troposphere, with implications for Bragg scattering studies and the theory of turbulence in general. This study will help the ecology of research better understand the laws of biological activity.

Range and Doppler reconstruction for sparse frequency agile linear frequency modulation‐orthogonal frequency division multiplexing radar

Sparse frequency agile linear frequency modulation-orthogonal frequency division multiplexing (LFM-OFDM) radar can improve anti-interference ability as well as reduce the sampling rate of the radar system. However, the frequency agility makes it difficult to realize coherent processing by using the fast Fourier transform. To overcome this problem, a signal processing scheme for the sparse frequency agile LFM-OFDM radar is proposed to obtain the high range and Doppler resolution in this study. The subcarriers are synthesised to an LFM signal in the time domain at first. Then, within the framework of the compressed sensing theory, an improved orthogonal matching pursuit algorithm is proposed to obtain the high-resolution range-velocity profile while reducing the computation complexity. Finally, several numerical simulations are provided to verify the effectiveness of the proposed method for moving targets.

Multi-output Convolutional Neural Network Based Distance and Velocity Estimation Technique for Orthogonal Frequency Division Multiplexing Radar Systems

The objective of this work is to propose a new method of estimating velocity and distance based on multi-output convolutional neural network (CNN) for orthogonal frequency division multiplexing (OFDM) radars. The two-dimensional (2D) periodogram is extracted from the received reflected waveforms through radar signal processing of received OFDM symbols. Conventionally, constant false alarm rate (CFAR) algorithm is used to estimate distance and velocity of targets. In contrast, this paper proposes a novel deep-learning based approach for the estimation of the targets in OFDM radar systems. The proposed multi-output CNN-based target detector estimates the distance and velocity of the target simultaneously. The proposed technique is verified through computer simulation. The results show that the proposed multi-output CNN-based method demonstrates more accurate distance and speed estimates than the conventional CFAR. Specifically, the distance and speed estimates of the proposed method are 9.8 and 12.3 times accurate, respectively, than those of the conventional CFAR.

Low probability of intercept‐based OFDM radar waveform design for target time delay estimation in a cooperative radar‐communications system

In this study, a low probability of intercept (LPI)-based orthogonal frequency division multiplexing radar waveform design strategy is developed for target time delay estimation in a cooperative radar-communications system, where the communications base station (CBS) is able to receive and process the radar emissions. The basis of the LPI-based radar waveform design strategy is to utilise the optimisation technique to design the transmitted waveform of a radar system for specified target time delay estimation accuracy in order to achieve enhanced LPI performance. The expression for Cramer–Rao lower bound is analytically derived and utilised as a performance metric for target time delay estimation performance. The resulting optimisation problem is solved by the approach of linear programming. Several numerical results are provided to verify the superiority of the proposed radar waveform design algorithm in terms of the LPI performance of the radar system. It is also shown that the radar transmitted power can be significantly reduced with the help from the CBS which plays a role of the bistatic radar receiver.

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

Target scene frequency diversity exploitation with ultra‐wideband orthogonal frequency division multiplexing radar

This paper concerns experimental investigation of the frequency-domain approach to target scene sensing using ultra-wideband orthogonal frequency division multiplexing software-defined radar. Individual spectral components of the radar signal (sub-carriers) are analysed with the aim of performing their adaptive selection and establishing similarity of the observed response to the previously collected responses of various target scenes. By performing this analysis, the authors are effectively utilising frequency diversity of targets for detection purposes. A low-power, short-range radar system built at Miami University is used to apply this approach to target detection with generalised-likelihood ratio test (GLRT) and frequency profile matching (FPM). Experimental results indicate good promise of FPM, which performed equally to, or outperformed GLRT in all scenarios. Results of correct detection and false alarm rates are shown and discussed, along with theoretical descriptions of the detection approaches.

Systematic approach in designing wavelet packet modulation‐orthogonal frequency division multiplexing radar signal by applying the criterion of least‐squares

In recent years, wavelet packet modulation-orthogonal frequency division multiplexing (WPM-OFDM) signals have been introduced for radar applications. These signals have some significant properties such as inherent high range resolution, high resistance of radar system against jamming reception and improved target detection performance in contrast with common traditional signals. However, there is no systematic method for designing WPM-OFDM signals to be used in radar applications. In the present study, the authors have started solving the problem of designing a WPM-OFDM radar signal under a criterion of minimising the least-squares error between designed and desired ambiguity functions. A thumbtack shape is assumed to be the ideal shape of the ambiguity function. In the following, an iterative algorithm is introduced to allocate a proper phase to the desired ambiguity function for obtaining better results. In this study, it is shown that this algorithm can reduce side-lobes, throughout the entire plane of the ambiguity function; therefore using the mentioned algorithm leads to having a desired signal for a radar application. Consequently, by extending the presented method, a pair of WPM-OFDM signals is simultaneously designed which obtain their cross ambiguity function to approximate a desired one under the criterion of least-squares.

Orthogonal frequency-division multiplexing radar signal design with optimised ambiguity function and low peak-to-average power ratio

Considering the important role of the ambiguity function (AF) of a signal regarding the performance of a matched filter bank for the detection of targets and the estimation of their ranges and velocities, the thumbtack shape is assumed to be the desirable shape of the AF and the method of least squares for the synthesis of the AF is introduced. Then, an iterative method for the allocation of a proper phase to the desired AF is proposed to obtain better results. This method is then applied to select the proper codes for the synthesis of pulsed orthogonal frequency-division multiplexing signals. It is also shown how this method can reduce sidelobes, almost uniformly, throughout the entire ambiguity plane. Finally, an efficient algorithm is presented, which modifies the produced codes in order to reach a lower peak-to-average power ratio suitable for transmission.