Optimization of single transmit pulse shape to maximize detection and identification of ground mobile targets

Garren, David A.; Osborn, M.K.; Odom, A.C.; Goldstein, J.S.; Pillai, S.U.; Guerci, J.R.

doi:10.1109/acssc.2000.911247

Cited by 3 publications

(5 citation statements)

References 4 publications

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“…The optimization of the transmission pulse shaping in order to maximize target identification performance that was developed by Guerci and Pillai [9] is extended to include multiple channels, colored noise, and non-zero colored clutter. These extensions [11] for the identification problem are developed via a maximization of the Mahalanobis distance, and thus the probability of correct classification, between the echoes of two target classes.…”

Section: Resultsmentioning

confidence: 99%

Optimal Target Identification via Adaptive Radar Transmission

Garren¹,

Osborn²,

Odom³

et al. 2000

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-This paper investigates the optimization of both single and full polarization radar transmission waveforms to maximize target identification discrimination. This theory is applied to the discrimination of the T-72 and Ml battle tanks based upon simulated target frequency response data. Significant performance improvement in identification is obtained using an optimized transmission waveform over that of a standard chirped pulse. generated using the Fast Illinois Solver Code Q^ISC) that applies a method-of-moments technique to provide high fidelity at relatively low radar frequencies. The specific VHFband data generated by S AIC-Champaign cover frequencies between 225-375 MHz at an aspect interval of 2°.

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Section: Resultsmentioning

confidence: 99%

Optimal Target Identification via Adaptive Radar Transmission

Garren¹,

Osborn²,

Odom³

et al. 2000

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“…As present in [2], for the case of stationary colored noise and clutter, the maximization of the probability of correct classification ( CC P ) is equivalent to the maximization of the Mahalanobis distance. So we define the relative Mahalanobis distance ( R MD ) to quantificationally describe the impact of the aspect variation on the CC P as follows:…”

Section: B Impact Of Target Aspect Variation On Optimal Waveform Andmentioning

confidence: 99%

“…To date, the optimal waveform design methods in most literature for determined TIR are all based on this fact, and the target aspect is assumed to known exactly and without variations. The optimal waveform concentrates its energy to single narrow band corresponding to the strongest response in the frequency spectrum of TIR, and will change a lot if aspect varies [2].…”

Section: B Impact Of Target Aspect Variation On Optimal Waveform Andmentioning

confidence: 99%

“…To solve this problem, we expect the real-time target aspect be provided by tracking as described in [2], [7]. However, two aspects must be considered in cognitive radar: first, the optimal waveform for target track and recognition is greatly different, the frequent and fast switch of waveform is hard to realize; second, accurate tracking when recognizing target will cause resources waste and disagrees with the task of dealing with multiple target.…”

Section: Introductionmentioning

confidence: 99%

“…Maximization a certain distance (Mahalanobis distance [2]- [4], matched distance [5] etc.) between targets is a widely used criterion.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive waveform design based on LSSVM for moving target recognition in cognitive radar

Fan

Liao

Ding³

et al. 2012

2012 IEEE International Conference on Information Science and Technology

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The optimal waveform for extended target recognition is directly affected by the target impulse response, which is sensitive to the target aspect. Hence, the variation of target aspect needs to be considered when the target is moving. Aiming at this problem, a new framework of cognitive radar is proposed. It predicts the new aspect via least square support vector machines (LSSVM) by using the prior knowledge of target aspect, and then obtains the optimal waveform based on not only the updated prior probabilities of the target hypothesis but also the updated TIR in a circular of interrogation. Simulations part shows the loss of recognition efficiency for a moving target when treated as static by the method in previous literature, and proves the validity of the proposed method.

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Optimal transmission pulse shape for detection and identification with uncertain target aspect

Garren

Osborn

Odom

et al.

Proceedings of the 2001 IEEE Radar Conference (Cat. No.01CH37200)

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This paper investigates the optimization of the transmission radar pulse shape to maximize either target detection or identity discrimination between the T-72 and M1 tanks under conditions of aspect uncertainty, Significant performance improvements in detection and identification are obtained using optimized transmission waveforms over that of standard chirped pulses. tion discrimination using two simulated surface mobile targets: the T-72 and M1 main battle tanks. SAICChampaign [S] generated VHF-band and X-band radar signatures for a single elevation angle of 15" and the full spectrum 0" -360" of aspect angles relative to the sensor. The X-band data cover frequencies between 9.28-9.92 GHz, whereas the VHF-band data span 225-375MHz.

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Optimization of single transmit pulse shape to maximize detection and identification of ground mobile targets

Cited by 3 publications

References 4 publications

Optimal Target Identification via Adaptive Radar Transmission

Optimal Target Identification via Adaptive Radar Transmission

Adaptive waveform design based on LSSVM for moving target recognition in cognitive radar

Optimal transmission pulse shape for detection and identification with uncertain target aspect

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