Phase-coded waveforms for radar

Davis, R. M.; Fante, Ronald L.; Perry, R.P.

doi:10.1109/taes.2007.357142

Cited by 69 publications

(47 citation statements)

References 7 publications

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“…The design of one-dimensional, low-sidelobe mismatch pulse-compression filters has been widely treated in the radar literature [5], [6], [7]. In one-dimensional MMP, the pulsecompression filter is constructed as follows.…”

Section: A Backgroundmentioning

confidence: 99%

“…Finally, as we show in the next subsection, if the radar repeats the same waveform on each pulse, the STAMMP filter decomposes into MMF pulse-compression [5], [6], [7] followed by conventional STAP clutter suppression. Thus, in the repeated waveform case, STAMMP has no advantage over conventional factored processing.…”

Section: G Comparison With Other Mmp Approachesmentioning

confidence: 99%

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Space-time adaptive mismatch processing

O'Connor

Kantor

Jakabosky

2016

2016 IEEE Radar Conference (RadarConf)

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Conventional signal processing for GMTI radar (pulse-compression and STAP clutter-cancellation applied sequentially) results in significant losses when pulse-to-pulse waveform diversity is used, because of range-sidelobe modulation. This report describes STAMMP, a method for joint pulse-compression, beamforming, and Doppler processing that mitigates rangesidelobe modulation. The method is partially-adaptive and uses a small number of adaptive degrees of freedom to ensure the filters are robust to radar pointing and calibration errors. SINR is evaluated in a GMTI radar simulation and STAMMP is shown to outperform conventional factored processing approaches.

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Section: A Backgroundmentioning

confidence: 99%

Section: G Comparison With Other Mmp Approachesmentioning

confidence: 99%

Space-time adaptive mismatch processing

O'Connor

Kantor

Jakabosky

2016

2016 IEEE Radar Conference (RadarConf)

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“…The N=11 Barker pattern is seen to be a markedly inferior code choice in both our inverse filter strategies (this N=11 phenomenon was also reported in [8]), while N=13 Barker is superb in every regard! Almost all papers dealing with inverse filtering [4], [8]- [11] seem to have taken a two-stage approach: settling at the outset on a code with good standalone credentials (like MPS) and offering that up for "bolt-on" filtering. Our view is that the bolt-on approach can never be relied upon to give optimal sidelobe reduction.…”

Section: Our Policy On Code Selectionmentioning

confidence: 99%

Reducing pulse compression sidelobes by inversion-amenable code selection

Cain

Yardim

Bowler³

et al. 2008

2008 IEEE Radar Conference

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Two alternative filtering approaches (dubbed "Code-Inverse" and "CodeACF-Inverse") for reduction of tempo-ral sidelobes are evaluated and compared for practical engineeering application to pulse compression. It is seen that the optimal code pattern for each code length must be discovered as part of a tightly integrated search process that is sensitive to the inverse filter design algorithm and the number of coefficients budgeted. Re-use of codes derived in other contexts has been commonplace in earlier work, but rarely proves optimal. Hence unique application algorithm-specific codes must be sought, with codewords for CodeACF-Inverse employment being obtained independently from those for Code-Inverse usage. If CodeACF-Inverse's greater storage requirement can be accommodated, then it is found to be very significantly superior. A rule-of-thumb that filter length should be about three times the code length is confirmed by measured sidelobe performance when code sequences are chosen to be optimally amenable to inverse filtering.

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“…Since the conception of pulse compression technique, many works have been published regarding phase and frequency modulation of the transmit waveform [1][2][3][4][5] and matched and mismatched receiver filter design [6][7][8]. In the referred studies, there are some basic features that are always at stake to be enhanced.…”

Section: Introductionmentioning

confidence: 99%

Stochastic analysis of random frequency modulated waveforms for noise radar systems

Pralon

Pompeo

Fortes

2015

IEEE Trans. Aerosp. Electron. Syst.

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Noise radars are electromagnetic systems that use random signals for detecting and locating reflecting objects. Besides high performance against external interferences (intentional or not), the stochastic nature of the transmitted waveforms may lead to the suppression of range ambiguity in the detection of targets and low range sidelobes, if systems parameters are properly chosen. This paper addresses a probabilistic analysis to derive mathematical expressions for the signal-to-noise ratios, the peak-to-sidelobe ratios and the signal-to-interference ratios (due to ambiguous targets) throughout a typical receiver processing chain of a pulsed FM noise radar. A receiver that employs matched filtering and pulse integration prior to detection was considered. Pulse compression and integration gains (in signal-to-noise and signal-to-interference, due to ambiguous targets, ratios) are also derived. The analysis provides closed-form expressions relating the precise dependence of sidelobe levels as well as interference levels due to ambiguous targets to the integration time, the transmit signal bandwidth, and the number of integrated pulses.

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Phase-coded waveforms for radar

Cited by 69 publications

References 7 publications

Space-time adaptive mismatch processing

Space-time adaptive mismatch processing

Reducing pulse compression sidelobes by inversion-amenable code selection

Stochastic analysis of random frequency modulated waveforms for noise radar systems

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