# Chirp Signals and Noisy Waveforms for Solid-State Surveillance Radars

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## Abstract

**:**

## 1. Introduction

- the longer time duration allows to lower the transmitted peak power (with respect to an equivalent pulse compression radar) by about a figure of approximately 30 times, keeping unchanged the overall system requirements (e.g., maximum range, range resolution, bandwidth allocation) for the same application;
- the lower transmitted power calls for less solid-state modules to be combined, easing the radar transmitter architecture;

## 2. Deterministic Waveforms Design

## 3. Noise Radar Technology

^{1492}[36], as implemented in Matlab generator—practically infinity), so that each radar can operate with its own radar signal, possibly different from the others. Being noisy, the waveforms themselves possess a low enough degree of mutual cross-correlation to pave the way for distributed MIMO operation with a low level of mutual interferences [27] even operating at the same, or nearby, carrier frequency.

#### 3.1. Power Budget

#### 3.2. Unimodular Pure Noise

#### 3.3. Range Sidelobe Suppression Algorithms

^{th}signal among the others. For this purpose, the CAN family also provides a “MIMO” version for the algorithms in which the quantity to be minimized is the difference between the obtained and the desired covariance matrix [25], until a stop criterion is reached.

## 4. Conclusions

## Author Contributions

## Conflicts of Interest

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**Figure 1.**Normalized amplitude weighting for Hybrid Non-Linear Frequency Modulation (HNLFM) (red line: optimum weighting, blue line: sub-optimum weighting).

**Figure 3.**Effect of the compression ratio BT on the Peak-to-Sidelobes Ratio (PSLR), HNLFM (optimum and sub-optimum) and Millet signals, the last is shown only as a historical reference.

**Figure 4.**Effect of the compression ratio BT on the compressed pulse width (${\mathsf{\tau}}_{3\mathrm{dB}}$).

**Figure 5.**HNLFM compressed pulse: $BT=128$, $T=128\mathsf{\mu}\mathrm{s}$, $B=1\mathrm{MHz}$. (

**a**) Normalized autocorrelation; (

**b**) Power spectrum density.

**Figure 6.**Pure noise generation block-diagram (ZMNL: Zero-Memory-Non-Linear transformation, FFT: Fast Fourier Transform, iFFT: inverse-FFT).

**Figure 7.**Spectra of Unimodular Pure Noise, and LFM. With $B=1\mathrm{MHz}$, $T=4096\mathsf{\mu}\mathrm{s}$.

**Figure 8.**Normalized autocorrelations of Unimodular Pure Noise and LFM: $B=1\mathrm{MHz}$, $T=4096\mathsf{\mu}\mathrm{s}$.

**Figure 9.**Compressed pulse comparison between Unimodular Noise: (

**a**) Stopband Cyclic Algorithm New (SCAN); (

**b**) Band Limited Algorithm for Sidelobes Attenuation (BLASA) Single Input, Single Output (SISO): B = 1 MHz, T = 4096 μs.

**Figure 10.**Spectrum comparison among Unimodular Noise, SCAN and BLASA SISO: B = 1 MHz, T = 4096 μs, M = 2.

**Figure 11.**Autocorrelation of BLASA Multiple-Input Multiple-Output (MIMO): B = 1 MHz, T = 256 μs, M = 2.

Algorithm | MIMO Version | Sidelobe Level and Suppression Interval | $\raisebox{1ex}{${\mathit{B}}_{\mathit{T}\mathit{O}\mathit{T}}$}\!\left/ \!\raisebox{-1ex}{${\mathit{B}}_{-\mathbf{3}\mathbf{d}\mathbf{B}}$}\right.$ | Amplitude Modulation |
---|---|---|---|---|

HNLFM | No | −67 dB at BT = 4096 | 400% | Pseudo trapezoidal AM |

Pure Unimodular Noise | No | −23 dB at BT = 4096 | 100% | Unimodular |

SCAN | No | −45 dB at BT = 4096 (within 15%) | 100% | Unimodular |

BLASA SISO | No | −50 dB at BT = 4096 | 100% | Unimodular |

BLASA MIMO | Yes | −30 dB at BT = 256 (within 12%) if unimodular amplitude with M = 2 | 400% | Unimodular |

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**MDPI and ACS Style**

Galati, G.; Pavan, G.; De Palo, F.
Chirp Signals and Noisy Waveforms for Solid-State Surveillance Radars. *Aerospace* **2017**, *4*, 15.
https://doi.org/10.3390/aerospace4010015

**AMA Style**

Galati G, Pavan G, De Palo F.
Chirp Signals and Noisy Waveforms for Solid-State Surveillance Radars. *Aerospace*. 2017; 4(1):15.
https://doi.org/10.3390/aerospace4010015

**Chicago/Turabian Style**

Galati, Gaspare, Gabriele Pavan, and Francesco De Palo.
2017. "Chirp Signals and Noisy Waveforms for Solid-State Surveillance Radars" *Aerospace* 4, no. 1: 15.
https://doi.org/10.3390/aerospace4010015