Polyphase Code Design for Orthogonal Netted Radar Systems

In this paper, we propose a general target model for multiple-input multiple-output (MIMO) radar. Two types of targets are presented. For each type of target, we develop a corresponding optimum waveform designing method to optimize detection performance. Based on Chernoff-Stein lemma, we use relative entropy as the performance measure. We show that the optimum waveform designing method can obtain better detection performance than traditional orthogonal waveform designing method.Keywords MIMO radar, waveform designing, relative entropy CitationTang J, Luo J, Tang B, et al. Target models and waveform design for detection in MIMO radar. Sci

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“…It is easy to verify that (18) is equivalent to (15). From Theorem 1, we find that we should choose V s = U w .…”

Section: Optimum Waveform Designing For Two Types Of Targetmentioning

confidence: 97%

“…Here we need to choose U s , Σ s and V s for solving the maximization problem given in (15). Theorem 1.…”

Section: Optimum Waveform Designing For Two Types Of Targetmentioning

confidence: 99%

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Target models and waveform design for detection in MIMO radar

Tang

Luo

Tang

et al. 2012

Sci. China Inf. Sci.

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“…Deng [2] derived a transmitted waveform with a certain level of pulse compression and pseudo-orthogonality by using a genetic algorithm. However, interferences due to the pseudo-orthogonality deteriorated the performance of the MIMO radar.…”

Section: Introductionmentioning

confidence: 99%

A MIMO radar code construction based on space–time coded complementary codes

2016

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Pulse compression is used to improve range resolution and detectability of various radar systems. A multiple-input multiple-output (MIMO) radar is required to transmit an orthogonal code set from a transmit-antenna element. However, the design of a code set with orthogonality as well as good pulse compression properties for a MIMO radar is a difficult problem. Although complementary codes have an ideal pulse compression property, they have no cross-orthogonality. In this paper, we propose two code construction schemes based on space-time coding using complementary codes. The number of code sets and transmit-antenna elements can be easily extended by the proposed construction schemes.

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“…Several phase coded waveforms have been proposed previously [7]- [10] with good autocorrelation and crosscorrelation properties. These waveforms are designed for good delay and Doppler resolution characteristics but spatial resolution characteristics are not considered.…”

Section: Introductionmentioning

confidence: 99%

MIMO Radar Ambiguity Optimization using Phase Coded Pulse Waveforms

Sharma¹,

Rajeswari²

2013

IJCA

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Multiple input multiple output radars transmit partially coherent or noncoherent waveforms for improving spatial resolution or spatial diversity. While waveform design for SIMO radars concentrate on improving the delay and Doppler resolution characteristics, waveform design for MIMO radars involve optimization of delay, Doppler and spatial resolution characteristics. The resolution properties of MIMO radar transmit waveforms is studied using the MIMO radar ambiguity function. MIMO radar ambiguity function of frequency hopping waveforms is recently derived. Considering the many advantages of phase coded pulse waveforms in radar applications, this paper derives the MIMO radar ambiguity function of phased coded pulse waveforms. Further, a numerical optimization algorithm based on simulated annealing is proposed for designing parameters of the phase coded pulse waveforms that minimize the peak of the ambiguity function at all mismatched values of delay, Doppler and angular dimensions.

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Polyphase Code Design for Orthogonal Netted Radar Systems

Cited by 384 publications

References 21 publications

Target models and waveform design for detection in MIMO radar

Target models and waveform design for detection in MIMO radar

A MIMO radar code construction based on space–time coded complementary codes

MIMO Radar Ambiguity Optimization using Phase Coded Pulse Waveforms

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