The Constant Information Radar
Abstract
:1. Introduction
1.1. Background
1.2. Contributions
- Review the estimation rate for tracking radars
- Examine the traditional target Kalman model
- Augment tracking to include predicted estimation information
- Motivate CIR radar using predicted information
- Demonstrate the results of the CIR in a simulation compared to a traditional radar
2. Radar Tracking and Measurement Model
2.1. Target Motion Model
2.2. Target Measurement Model
3. Target Tracking Information
3.1. Radar Estimation Rate
3.2. Target Predicted Information
Algorithm 1 Revisit Time Modulation (Solving for T) |
|
4. Revisit Time Modulation
4.1. Model Mismatch
4.2. Signal-to-Noise Ratio
5. Examples
5.1. Looping Track (Model Mismatch Modulation)
5.2. Approaching Radial Track (SNR Modulation)
5.3. Evasive Track (Global and Local Trending)
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Parameter | Value | Parameter | Value |
---|---|---|---|
Bandwidth (B) | 5 MHz | Center Frequency () | 3 GHz |
Absolute Temperature () | 1000 K | Pulse Duration () | 5 µs |
Probability of False Alarm (P) | Radar Antenna Gain (G) | 30 dBi | |
Radar Transmit Power () | 100 kW | Target Cross-Section (σ) | 10 m |
Chirp Rate | Window Variance | ||
Wave Speed (c) | m/s | Number of Pulses () | 10 |
Varied | Number of Array Elements () | 10 |
Track | Traditional Radar | CIR |
---|---|---|
Looping Track | 99.500% (200 targets) | 99.870% (800 targets) |
Approaching Radial Track | 99.000% (100 targets) | 99.834% (600 targets) |
Evasive Track | 99.750% (400 targets) | 99.940% (1700 targets) |
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Paul, B.; Bliss, D.W. The Constant Information Radar. Entropy 2016, 18, 338. https://doi.org/10.3390/e18090338
Paul B, Bliss DW. The Constant Information Radar. Entropy. 2016; 18(9):338. https://doi.org/10.3390/e18090338
Chicago/Turabian StylePaul, Bryan, and Daniel W. Bliss. 2016. "The Constant Information Radar" Entropy 18, no. 9: 338. https://doi.org/10.3390/e18090338