Electronics

Download Adaptive High-Resolution Sensor Waveform Design for Tracking by Ioannis Kyriakides, Darryl Morrell, Antonia PDF

By Ioannis Kyriakides, Darryl Morrell, Antonia Papandreou-Suppappola, Andreas Spanias

Contemporary options in sleek radar for designing transmitted waveforms, coupled with new algorithms for adaptively settling on the waveform parameters at whenever step, have ended in advancements in monitoring functionality. Of specific curiosity are waveforms that may be mathematically designed to have diminished ambiguity functionality sidelobes, as their use may end up in a rise within the aim nation estimation accuracy. in addition, adaptively positioning the sidelobes can exhibit susceptible goal returns via lowering interference from enhanced pursuits. The manuscript offers an summary of modern advances within the layout of multicarrier phase-coded waveforms in response to Bjorck constant-amplitude zero-autocorrelation (CAZAC) sequences to be used in an adaptive waveform choice scheme for mutliple aim monitoring. The adaptive waveform layout is formulated utilizing sequential Monte Carlo suggestions that have to be matched to the excessive answer measurements. The paintings should be of curiosity to either practitioners and researchers in radar in addition to to researchers in different functions the place excessive answer measurements could have major advantages. desk of Contents: creation / Radar Waveform layout / objective monitoring with a Particle clear out / unmarried goal monitoring with LFM and CAZAC Sequences / a number of goal monitoring / Conclusions

Show description

Read or Download Adaptive High-Resolution Sensor Waveform Design for Tracking (Synthesis Lectures on Algorith and Software in Engineering) PDF

Best electronics books

Networked multisensor decision and estimation fusion : based on advanced mathematical methods

''Multisource details fusion has develop into an important strategy in components similar to sensor networks, house know-how, air site visitors keep an eye on, army engineering, communications, business regulate, agriculture, and environmental engineering. Exploring contemporary signficant effects, this booklet provides crucial mathematical descriptions and strategies for multisensory selection and estimation fusion.

Additional info for Adaptive High-Resolution Sensor Waveform Design for Tracking (Synthesis Lectures on Algorith and Software in Engineering)

Sample text

A sample code for the SIRPF is provided in Appendix C. 3 LIKELIHOOD PF In the Björck CAZAC case, the likelihood is very concentrated. Although this is good for measurement accuracy, the SIRPF will not work in this case as particles sampled from the broadly spread prior will not satisfy the likelihood easily. With the LPF, we sample values from the likelihood as it is more concentrated than the prior in the Björck CAZAC case. To achieve this, we evaluate the likelihood values at discrete bins of the delay-Doppler space of size T and ν.

31 CHAPTER 4 Single Target tracking with LFM and CAZAC Sequences In this chapter, we describe a sampling importance resampling particle filter (SIRPF) and a likelihood particle filter (LPF) [4] for the radar tracking problem. The SIRPF commonly uses the prior density as the importance density. However, when the likelihood is much more concentrated than the prior, samples proposed from the prior will be spread and, thus, will receive low weights when weighted with the likelihood. Therefore, the LPF is employed that uses the likelihood as the importance density.

Therefore, a particle filtering approach reduces approximation errors and the computational expense at the matched filter stage of the receiver. 31 CHAPTER 4 Single Target tracking with LFM and CAZAC Sequences In this chapter, we describe a sampling importance resampling particle filter (SIRPF) and a likelihood particle filter (LPF) [4] for the radar tracking problem. The SIRPF commonly uses the prior density as the importance density. However, when the likelihood is much more concentrated than the prior, samples proposed from the prior will be spread and, thus, will receive low weights when weighted with the likelihood.

Download PDF sample

Rated 4.99 of 5 – based on 37 votes