Continuous Wave Radars–monostatic, Multistatic and Network

Kulpa, Krzysztof

doi:10.1007/1-4020-4295-7_10

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…This kind of radar cannot determine the distance to the target. It only evaluates the frequency shifted away from the transmitted frequency based on the Doppler effect, and thus can render the radar immune to the interference from large stationary objects and slow moving clutter [2]. As the UCW radar is small in size, inexpensive to manufacture, relatively free from failure, and cheap to maintain, it has many potential applications.…”

Section: A Background and Motivationmentioning

confidence: 99%

“…In our case, since the received signals in (2) are functions of f k and h k , by the chain rule, J r ξ k can be expressed in an alternative form:…”

Section: Bayesian Fisher Information Matrixmentioning

confidence: 99%

“…The CW radar, on the other hand, is a type of radar system where a known stable frequency continuous wave signal is transmitted. Unique features of CW radars are lack of ambiguity, very low transmitted power and good electromagnetic compatibility [2]. These possible advantages of the CW radar have provided the motivation to explore their capability in various contexts such as target tracking [1], recognition [3], [4] and imaging [5].…”

Section: A Background and Motivationmentioning

confidence: 99%

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Power Allocation Algorithm for Target Tracking in Unmodulated Continuous Wave Radar Network

et al. 2015

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Unmodulated continuous wave (UCW) radar has been shown to have many unique features. With the recent development, UCW radar network has become an attractive platform for target tracking. In practice, to achieve better tracking performance, UCW radars are supposed to maximize their transmitted power, which may be in contradiction with the limited energy resources of themselves. Therefore, a performancedriven power allocation algorithm for Doppler-only target tracking in a UCW radar network is proposed. This algorithm can be viewed as a reaction of the cognitive transmitter to the environment perceived by the receiver to minimize the target state estimation mean square error with a given total power budget. The Bayesian Cramér-Rao lower bound gives a measure of the achievable optimum performance for target tracking and, importantly, it can be calculated predictively. Therefore, it is derived and utilized as an optimization criterion for the power allocation algorithm. The resulting optimization problem is proved to be convex, and hence, can be solved by gradient projection method. Numerical results show that the target tracking accuracy can be efficiently improved by the proposed algorithm.Index Terms-Bayesian Cramér-Rao lower bound (BCRLB), convex optimization, power allocation, target tracking, unmodulated continuous wave (UCW) radar.

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Section: A Background and Motivationmentioning

confidence: 99%

“…In our case, since the received signals in (2) are functions of f k and h k , by the chain rule, J r ξ k can be expressed in an alternative form:…”

Section: Bayesian Fisher Information Matrixmentioning

confidence: 99%

Section: A Background and Motivationmentioning

confidence: 99%

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Power Allocation Algorithm for Target Tracking in Unmodulated Continuous Wave Radar Network

et al. 2015

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“…Because the target's range and relative velocity are unknown, it is necessary to apply a set of filters matched to all possible range-velocity pairs. These matched filters are conjugated time-Doppler shifted versions of the transmitted signal [6]. This bank of filters can be implemented by using the Fourier Transform…”

Section: Matched Filter Processingmentioning

confidence: 99%

“…This removes the major contribution from the clutter and the direct path signal. This step is then typically followed by a range-Doppler matched filtering [6]. However, the Doppler sidelobes of the matched filter will reduce detection performance, in particular in presence of ICM.…”

Section: Introductionmentioning

confidence: 98%

Optimum Target Detection using Illuminators of Opportunity

Kubica

Neyt

et al.

2006 IEEE Conference on Radar

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Unlike classical bistatic radars, passive radars make use of illuminators of opportunity to detect targets and to estimate target parameters. One existing radio transmission suitable for passive radar operation is the Global System for Mobile Communication (GSM).For non-cooperative bistatic configurations, one of the major difficulties is the estimation of the reference signal which is required to perform detection. This reference signal, a priori unknown, can be extracted from the signal received at the antenna array provided the direction of arrival of the direct path signal is known.Conventional matched-filter based Doppler filtering offers the possibility of placing the target and interferences in a domain where they can be separated based on Doppler shift. However, slow moving targets residing near mainbeam clutter in the rangeDoppler diagram, remain difficult to detect. Internal Clutter Motion (ICM) exacerbates this issue by spreading the clutter signal power in Doppler frequency.In this paper, we first present a method to estimate autonomously the direction of the illuminating GSM base station from measurements obtained with a two-element antenna array. We passively detect the azimuth of the transmitter without a priori knowledge of the environment. Spatial processing is then employed to attenuate the direct path signal and mitigate its influence on the target detection process. We then propose two methods able to cope with clutter echoes with non zero-Doppler components. We first propose an extension of a CLEAN-like algorithm. We also propose to extend adaptive matched filters to noise-like signals. The adapted matched filter can be used to suppress strictly static clutter but also clutter affected by ICM. These methods are validated by using actual clutter measurements obtained from a passive radar using a GSM base station as illuminator of opportunity.

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