Potential pitfalls of cognitive radars

2019

In this work we address the problem of radar waveform optimization and target tracking. We propose an algorithm for optimal waveform design and target tracking based on the Control theoretic approach, where the waveform parameters are adaptively designed by minimizing the tracking mean square error (MSE). In this work we take several approaches to enhance the radar tracking performance. In a first place the Kalman filter was used to estimate the target position which we use to optimize the waveform parameters. Experimental results demonstrated the ability of the proposed algorithm to track a flying target in the Cartesian space, by providing accurate estimates of the target position and the target speed cartesian vector as well as the radial speed. The algorithm adapted the waveform parameters on the fly based on the estimate vectors. In literature, the doppler effect theory was intensively used to estimate target velocity. Under certain conditions, such as tracking high speed targe...

2010 International Waveform Diversity and Design Conference, 2010

In this paper, we propose a cognitive radar system for target tracking in the presence of multipath reflections. We exploit the inherent spatial diversity offered by the multipath environment by constructing a new measurement vector, which we refer to as a virtual measurement vector. We employ broadband Orthogonal Frequency Division Multiplexing (OFDM) signalling at the transmitter and implement adaptive waveform design by minimizing the posterior Cramér Rao bound (PCRB) on the target state estimates to find the optimal weights to be transmitted on each subcarrier bin of the OFDM signal. We demonstrate with numerical simulations that the mean square error in the case of a cognitive radar is significantly lower than the mean square error in the case of a standard radar.

The spectrum scarcity problem is occurred due to static allocation of the spectrum and increasing no of applications of the wireless communication. The same problem occurs in the field of radar communication. The solution of the said problem is a cognitive radio. The cognitive radio works on the on the principle of dynamic access. The essential part of the dynamic access is the spectrum sensing. In this paper an overview of the spectrum sensing techniques in Cognitive RADAR is given available in open literature. These techniques will help in the development of self-aware, environment aware RADAR systems which can adapt the target variations in a real time within a short interval of time.

International Conference on Graphic and Image Processing (ICGIP 2011), 2011

In this paper, we consider cognitive radar security in the presence of interceptors. By designing waveform, the cognitive radar will spread its most power to match the target channel for estimation and remove the spectrum that matches the interception channel for security. We firstly propose the signal model of a typical scenario, and then use the mutual information criterion to guide waveform design. By solving a convex optimization problem, we can obtain a globally optimal waveform. This paper also presents numerical examples to verify effectiveness of the idea and the approaches.

2010

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

International Journal of Communications, Network and System Sciences, 2016

Adjusting radar transmitted waveform to its environment is one of the most important roles in cognitive radar; having the capability of updating transmitted waveforms in different applications is a key point. It has been shown in many studies that if the waveform is designed according to the target and clutter characteristics, the detection performance will improve significantly. The uncertainty of the target radar signatures decreases via maximizing MI and the probability of extended target detection is increases via maximizing SNR. In this paper, a waveform design approach based on maximizing both SNR and MI and with regard to target and clutter shape is presented. The detection performance for proposed waveform is compared with previous proposed waveforms. The present paper compares different scenarios of target and clutter and using the probability of detection as a cost function to investigate the advantages and disadvantages of each waveform in different scenarios which are mainly discussed in this text. The desired waveform for cognitive radar is selected based on simultaneously making compromises between SNR and MI, which plays an important role in cognitive radar systems and based on the assumption addressed in the text, the best waveform transmitted into the environment.

IEEE Access

The majority of the current dual function radar-communication (DFRC) systems are producing only an angle-dependent transmit beampattern (BP) and imposing a constraint for the communication receiver to be present within the sidelobe (SL) directions to decode the transmitted information. In this paper, an efficient angle-range dependent DFRC system is proposed using frequency diverse array (FDA)-multipleinput multiple-output (MIMO) configuration. We developed a closed-loop design that improves the tracking task of the system and permits a cognitive selection for an optimum signaling strategy towards the intended communication receiver during each scan. We used two information embedding schemes, a proposed amplitude phase shift keying (APSK) and phase-shift keying (PSK), that utilize either the magnitude ratios and/or phase shifts between the radar waveform pairs towards the communication direction. Hence, the communication link is maintained and the system throughput is enhanced. The simulation results verify that the communication performance is enhanced in terms of low symbol error rate (SER), secure information transmission, and increased throughput, while for radar applications the performance is improved in terms of target detection and parameter estimation. It also showed that the proposed symbol mapping APSK scheme provides a high data rate transmission compared to the existing SL-based information embedding schemes while preserving a low bit error rate (BER). Besides, the Cramer-Rao lower bounds (CRLB) for range and angle estimation and the signal-to-interference-noise ratio (SINR) for the proposed DFRC system are analyzed. INDEX TERMS Radar signal processing, joint radar-communication, radio spectrum management, frequency diverse array.

Circuits, Systems, and Signal Processing

Many radar detection algorithms that assume a stationary environment (clutter) have been proposed and analyzed over the years. However, in practice, changes in the nonstationary environment can perturb the parameters of the clutter distribution, or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which are required to rapidly realize the nonstationarity, accurately learn the new characteristics of the environments, and adaptively update the detector. In this paper, aiming to develop a fully cognitive radar for target detection in nonstationary environments, we propose a unifying framework that integrates (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/ identification of clutter distribution by applying sparse theory and kernel density estimation methods, and (iii) adaptive target detection by automatically modifying the likelihood-ratio test and corresponding detection threshold. Further, with extensive numerical examples, we demonstrate the achieved improvements in detection performance due to the proposed framework in comparison

IETE Journal of Research, 2020

Cognitive Radar is a recently presented research topic, in which most efforts has been done for its conceptual description and the adaptive waveform design feature of these radars, while other aspects of additivity for optimum performance of cognitive radars has been ignored. In this paper, a framework for adaptive time resource management in Cognitive Radars is proposed. The main purpose of this paper is proposing an algorithm for time resource management, with incorporation of adaptive waveform design capability of cognitive radars, to enhance the radar performance for an efficient time resource usage. After developing the equations of radar time resource management using adaptive waveform design, an implementable algorithm is proposed for this purpose and its performance is simulated and analysed. The results show that the proposed algorithm resulted in more efficient time resource management compared to the existing ones.

Sensors

Canada's third-generation HFSWR forms the foundation of a maritime domain awareness system that provides enforcement agencies with real-time persistent surveillance out to and beyond the 200 nautical mile exclusive economic zone (EEZ). Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band. Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users. Sense-and-adapt technologies ensure that the system instantaneously switches to a new vacant channel on the detection of another user or unwanted jamming signal. Adaptive signal processing techniques mitigate against electrical noise, interference and clutter. Sense-and-adapt techniques applied at the detector and tracker stages maximize the probability of track initiation whilst minimizing the probability of false or otherwise erroneous track data.