Single antenna time reversal detection of moving target

Parameters affecting target detection in VNIR and SWIR range

Time reversal explores the rich scattering in a multipath environment to achieve high target detectability. Multiple-input multiple-output (MIMO) radar is an emerging active sensing technology that uses diverse waveforms transmitted from widely spaced antennas to achieve increased target sensitivity when compared to standard phased arrays. In this paper, we combine MIMO radar with time reversal to automatically match waveforms to a scattering channel and further improve the performance of radar detection. We establish a radar target model in multipath rich environments and develop likelihood ratio tests for the proposed time-reversal MIMO radar (TR-MIMO). Numerical simulations demonstrate improved target detectability compared with the commonly used statistical MIMO strategy.

Currently, target detection usually requires long-time coherent integration and suffers the Doppler shift, due to the velocity of maneuvering targets. This paper has proposed a complete scheme, applying the fractional Fourier transform into the estimation of range and velocity parameters of targets. The radar signal processing technique is developed to measure the range and velocity of moving targets simultaneously in a single frequency-stepped burst without the long-time integration and avert the negative effect of Doppler shift.

Attentions have been focused on the moving target detection in a high-resolution sea clutter. This study commences with a proposal of median-based estimator to estimate the power spectrum of high-resolution sea clutter by the time series observed in adjacent range cells and time intervals. The estimator provides a robust estimation when just a few aberrant time series happen in observation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF) is designed to suppress the clutter prior to the pulse integration. Then, the residual clutter, the output of the BACSF, is modelled as spherically invariant random vector. Upon applying an adaptive normalised matched filter (ANMF) to the residual clutter, a residual clutter's ANMF detector is derived. Moreover, in high-resolution radar background, considering that the approximately stationary intervals of sea clutter and residual clutter are much shorter than the coherent processing interval, another heuristic block-ANMF detector is proposed. It can integrate more pulses and can achieve better performance than the ANMF detector does. This study concludes with the experiments of simulated target against the real sea clutter. The experimental results demonstrate that, when target's Doppler frequency is beyond strong clutter region, the ANMF detector and block-ANMF detector perform better in the residual clutter than in the clutter.

Receiver operating characteristic (ROC) analysis is performed by a curve, called ROC curve, plotted based on detection probability, P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , versus false alarm probability, P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> , and has been widely used as an evaluation tool for signal detection. Specifically, the area under an ROC curve (AUC) is calculated and used as a detection measure. Unfortunately, finding distributions of P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> and P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> to generate a continuous ROC curve is practically infeasible. This article investigates approaches to generating a discrete 2D ROC curve of ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> ) without appealing for probability distributions. Since P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> and P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> are determined by the same threshold τ to specify a detector, an ROC curve of ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> ) can only be used to evaluate the effectiveness of a detector but not target detectability (TD) and also not background suppressibility (BS). To address this issue, a 3D ROC curve is generated as a function of ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> , τ) by introducing a specific threshold parameter τ as a third independent variable. As a result, a 3D ROC curve along with its derived three 2D ROC curves of ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> ), ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub> , τ), and ( P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> , τ) can further be used to design new quantitative measures to evaluate the effectiveness of a detector and its TD and BS. To demonstrate the full utility of 3D ROC analysis in target detection, extensive experiments are performed on two types of targets, prior target detection and anomaly detection, to conduct a comprehensive analysis on 3D ROC curves using new designed detection measures to evaluate target/anomaly detection performance.

As a key technology of detection and tracking system, moving target detection and tracking has attracted a great deal of attention. To achieve the goal of tracking target, conventional methods have to complete the detection of targets firstly, and then track the target. However, such kind of approaches require using the method of constant false-alarm rate to detect the whole frame image received at that time, which not only reduces the detection efficiency but also degrades the performance of target tracking. In order to implement real-time monitoring divers and other small moving targets under the conditions of strong underwater noise and clutter interference, an interactive algorithm for moving target detection and tracking is proposed based on acoustic image, which jointly analyzes the target detection system and the target tracking system. In the target tracking unit, the interactive algorithm takes advantage of data interconnection to remove the false targets produced by target detection; extrapolates the target's track, and predicts the location that the target may appear at the next moment by employing the Kalman filter. These messages will be used as priori information in the detection unit. In the detection unit, first of all, a gate is established whose center is the position that the target tracking unit predicted. For the image received at the next moment, detection in the predicted gate in implemented by using the method of constant false-alarm rate, followed by feeding back the detection results to the tracking unit. Compared with existed methods, the proposed algorithm can effectively improve the target detection efficiency and tracking performance, providing a better approach to monitor underwater small targets.

Small infrared moving target detection has an important role in the sea-based infrared search and tracking, maritime area surveillance and other applications. This method aims to detect the small infrared moving targets with the sea-sky background. The present study proposes a detection algorithm for small infrared targets based on the spatio-temporal saliency fusion. The contourlet analysis and edge extraction are carried out in the concurrent design. In order to effectively suppress the background and improve the target signal-clutter ratio, the spectral residual method is combined with the abovementioned methods to reconstruct the target fusion saliency image. Then the target motion region is estimated based on the optical flow method for the fusion saliency image and it is matched with the target area of interest to achieve the moving target detection. Moreover, the pipeline filtering is introduced to achieve the target confirmation by multi-frame judgment, reduce false alarm rate and complete the moving target detection for the infrared image sequence. Experimental results show that the proposed algorithm can achieve continuous target detection and have a higher detection precision via real long wave infrared image sequences.

Objective: Advancement in radar technology is moved from single antenna based system to multiple antenna system. From the viewpoint of the radar performance improvement, analysis of low Radar Cross Section (RCS) target detectability in rich scattering environment is utmost important. Methods: From the perspective of the advancement of the radar signal processing, phased array radar and MIMO radar have been already explored. This paper deals with the phased-MIMO radar, exploiting coherence signal processing gain and waveform diversity. Joint combination of coherency and diversity will improve the radar performance. Improvements: This paper deals with the analysis on the trade-off between the coherency and spatial diversity. The superiority of phased-MIMO radar, over other two systems, has been presented with respect to some selected parameters as in this paper.

The design of high-resolution radars which can operate in theater involves a careful consideration of the radar’s radiated spectrum. While a wide bandwidth yields better target detectability and classification, it can also interfere with other devices and/or violate federal and international communication laws. Under the Army Research Laboratory (ARL) Partnerships in Research Transition (PIRT) program, we are developing a Stepped-Frequency Radar (SFR) which allows for manipulation of the radiated spectrum, while still maintaining an effective ultra-wide bandwidth for achieving good range resolution. The SFR is a forward-looking, ultra-wideband (UWB) imaging radar capable of detecting concealed targets. This paper presents the research and analysis undertaken during the design of the SFR which will eventually complement an existing ARL system, the Synchronous Impulse REconstruction (SIRE) radar. The SFR is capable of excising prohibited frequency bands, while maintaining the down-range resolution capability of the original SIRE radar. The SFR has two transmit antennas and a 16-element receive antenna array, and this configuration achieves suitable cross-range resolution for target detection. The SFR, like the SIRE radar, is a vehicle mounted, forward-looking, ground penetrating radar (GPR) capable of using synthetic aperture radar (SAR) technology for the detection of subsurface targets via 3D imaging. Many contradicting design considerations are analyzed in this paper. The selection of system bandwidth, antenna types, number of antennas, frequency synthesizers, digitizers, receive amplifiers, wideband splitters, and many other components are critical to the design of the SFR. Leveraging commercial components and SIRE sub-systems were design factors offering an expedited time to the initial implementation of the radar while reducing overall costs. This SFR design will result in an ARL asset to support obscured target detection such as improvised explosive devices (IEDs) and landmines.

A 2D UWB localization technique based on joint ToA/DoA in indoor dense multipath environment is proposed. In this method, direction of arrival (DoA) is estimated from time of arrival (ToA). The joint usage of ToA and DoA results in an accurate localization of the mobile node (MN). Unlike conventional methods, the proposed localization technique needs only one access point (AP) with an array structure. This consequently eases the synchronization requirement of the proposed localization scheme when compared to the classical ToA-based technique requiring 3 of more synchronized APs. To verify the proposed method real time UWB measurements in dense indoor multipath environment covering 2–6 GHz band were carried out. The results show that accurate 2D localization can be achieved using the proposed scheme. Furthermore, the accuracy performance of the proposed technique is compared to the classical ToA localization technique using more than 3 APs. The results, in terms of average range error, show that the ToA method slightly outperforms the proposed scheme for the LOS. However, for the NLOS the proposed scheme always provides a better position estimation (i.e. less average range error). For instance, the proposed technique provides an average range error of less than 2.3 cm for LOS and 12.3 cm for NLOS situations. The angular error is less than 0.5° and 1.48° for LOS and NLOS scenarios, respectively.

Infrared weak small target detection is one of the key technologies in the infrared early warning system, infrared imaging guidance system and wide-field view surveillance system etc. In the complex and low signal-to-noise ratio background environment, the target has only a few pixels. There is no shape and texture information to use. All of the above issues bring great difficulties to infrared dim-small target detection. In this paper, in order to deal with the shortcoming of large pixel tracking in moving target detection algorithm based on time domain filtering, apply the dim target detection based on Laplace operator to the subject of this paper, the false alarm points obviously to be less, and the target point is usually in the form of a single pixel, lay a good foundation for reducing the complexity of the algorithm.

Time reversal (TR) is a promising technique in detecting weak targets immersed in clutter. This paper reports a series of electromagnetic (EM) domain experiments on TR detection using a single antenna pair in a controlled scattering environment. The TR likelihood ratio detector is compared with the conventional energy detector and the matched filter. The EM experiments demonstrate the superiority of TR detection over conventional detection in rich multipath scattering environments.

Computer vision-based motion target detection and tracking, which is widely used in video surveillance, human-computer interaction, range interpretation, and other fields, is one of the current research hotspots in the field of computer vision. In engineering scenarios, the two are inseparable and need to work together to accomplish specific tasks. The related research is progressing rapidly, but there is still room for improving its timeliness, accuracy, and automation. In this paper, we summarize and classify some classical target detection methods, analyze the basic principles of convolutional neural networks, and analyze the classical detection algorithms based on region suggestion and deep regression networks. After that, we improve the SSD algorithm for the shortage of low-level feature convolution layers, which has insufficient feature extraction and leads to poor detection of small targets. For the motion target tracking problem, this paper studies the motion target tracking method based on support vector machine and proposes the tracking method of support vector regression and the corresponding online support vector regression solution method based on the analysis of support vector tracking method and structural support vector tracking method. In this paper, we propose a tracking method that fuses structural support vector machines and correlation filtering. The structure is based on the idea of Inception, which adds and replaces some feature convolution layers of the original network while maintaining the original lightweight backbone. The final experiments on the VOC data set demonstrate that the improved algorithm improves the average detection accuracy by 2.6% compared to the original algorithm and basically maintains the real-time speed as well. Experimental simulations on a subset of VOC data (human set) show a significant improvement in AP values and more effective and reliable detection tracking of moving targets. The stability and accuracy of motion target detection and tracking are improved by setting parameters, such as confidence level; the effectiveness and continuity of detection and tracking are judged by setting the interframe centroid distance.

This paper proposes an intelligent digital modeling system based on computer vision technology, aiming to realize real-time analysis and modeling of sports games. This study uses deep learning technology, combined with motion target detection and action recognition algorithms, to build an automated and intelligent sports game modeling system. The system captures game data in real time through video surveillance equipment, and uses target detection algorithms such as YOLO and SSD to identify athletes, balls and other game elements. At the same time, it realizes the accurate capture of athlete movements and tactical intentions based on the algorithm of posture estimation and action recognition. In terms of experimental verification, this paper takes football games as an example. The accuracy of the system in motion target detection is 92.5%, and the accuracy in athlete action recognition is 87.3<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>• In addition, the real-time modeling accuracy of the system is controlled within 5%, and the processing delay is less than 200 milliseconds, which meets the requirements of real-time analysis. Through the analysis of experimental results, this study proves the efficiency and accuracy of the system in complex sports game environments.

In this paper, we propose an Alamouti-code-based relaying scheme for frequency asynchronous amplify-and-forward (AF) relay networks. Both the oscillator frequency offsets and the Doppler shifts among the distributed nodes are considered in our design. We employ orthogonal frequency-division multiplexing (OFDM) modulation at the source node and let the two relay nodes implement only simple operations, such as time reversal, conjugation, and amplification. We show that without Doppler shifts, the multiple carrier frequency offsets (CFOs) can be directly compensated at the destination, and the received signals exhibit an Alamouti-like structure. We further prove that full spatial diversity can be achieved by the fast symbol-wise detection when the oscillator frequency offset between the relay nodes is smaller than a certain threshold, which yields lower decoding complexity compared with the existing schemes. In the case with Doppler shifts, where the direct CFO compensation becomes impossible, we develop a repetition-aided Alamouti coding approach, by which full diversity can be nearly achieved from the fast symbol-wise detection. Numerical results are provided to corroborate the proposed studies.