**1. Introduction**

With ultra-wide bandwidth, the ultra-wide band (UWB) signal is considered as an ideal locating technique in a short-range with high spatial resolution. As defined by the Federal Communications Commission (FCC), UWB technology has a center frequency higher than 2.5 GHz, or if less than 2.5 GHz, there must be a minimum bandwidth ratio of 0.2 [1], or the minimum bandwidth must reach 500 MHz [2]. To avoid affecting other narrow band systems, the rules of FCC allow the effective isotropic radiated power (EIRP) level of UWB devices to be lower than −41.3 dBm/MHz in the frequencies range of 3.1 to 10.6 GHz [3], so the UWB devices can work for more extended periods than narrow band systems with the same battery power, and due to the use of very narrow pulses, UWB signals are better able to penetrate in the nondestructive environments. General modulation techniques are used for UWB signals such as pulse amplitude modulations (PAMs), On-Off Keying (OOK), and pulse position modulation (PPM) [4]. One can use time-hopping (TH) in UWB systems to create TH-PPM, TH-BPSK signal types [5], or design a generator circuit which generates the 4-th and 5-th order derivative of Gaussian pulses in TH-QPSK system applied to multipath channels [6]. Each modulation technique has a different application range. The choice of the right modulation configuration not only increases the efficiency of system implementation but also maximizes the benefits of ultra-wide bandwidth and reduces the complexity of device hardware. In [7], a simple peak detection based on noncoherent UWB receiver is proposed for low data rate wireless sensor networks (WSN) and Internet of things (IoT) applications. It has improved receiver performance with TH-PPM UWB signal. In [8], to reduce the complexity of the TH-UWB receiver, a channel shortening equalizer design method is proposed based on an eigen filter using a new objective function, whereby the proposed system has dramatically reduced the power of channel impulse response, spectral distortion, multiaccess interference, and noise power. Therefore, different UWB signal modulation types have affected the quality and application of the UWB system.

In those modulation techniques, the PPM technique is one of the widely used configurations in UWB systems. Studies on UWB-PPM in wireless communication networks mainly focus on solutions to reduce the conflicts in multiuser access systems; for example, [9] proposed an M-ary PPM modulation configuration for the UWB (M-PPM) system and indicated that the proposed system significantly improved performance compared to systems using direct spreading sequences in the environments with a low signal to noise (SNR) ratio. In [10], Vinod Venkatesan et al. proposed the application of a direct spreading sequence with the optimized UWB-PPM technique for multiaccess systems. The proposed method reduced the impact of multiaccess interference (MAI) and significantly reduced the floor error compared to the orthogonal signal configuration at a large SNR ratio. Besides, there are several studies on improving the quality of the receiver for UWB-PPM signals [11], determining the optimal integration time for the energy detector of the UWB-PPM system [12], and developing a measurement matrix combined with randomly Fourier transform converters for UWB-PPM signals [13]. The combination of PPM symbols and time of arrival (TOA) estimation algorithm using the Sub-Nyquist IR-UWB signal in the IR-UWB device is discussed in [14]. Turbo codes for PPM-IR UWB signals to improve the power spectral density (PSD) power signal density [15] and randomizing the pulses to improve the UWB system [16] were proposed. The noncoherent modulation techniques based on the use of the receiver adaptive thresholds applied to enhanced PPM in the IR-UWB and the direct chaotic communication UWB (DCC-UWB) systems were proposed to improve the bit error rate (BER) performance of the system in a multipath transmission environment [17].

For testing purposes, material penetrating systems using UWB technology to examine nondestructive environments are discussed in [18]; the result indicated that this system can detect imperfect structures of metal. Besides that, the estimation of the layer's thickness based on the processing of the GPR's data with the optimized techniques (such as neural networks) is discussed in [19,20]. When using UWB technology in the testing, positioning, or another application in communication to improve the resolution of the systems, one of the main problems is choosing the appropriate modulation technique combined with the receiver's signal processing methods. The selection of a modulation scheme based on determination distance was discussed in [21]. From those results, we can recognize that the correct detection of UWB pulse signals is one of the essential factors which affect the accuracy of the distance estimation technique. In [22], an UWB indoor positioning system is presented to exploit two-way flight time to calculate range measurements to determine the transceiver location based on Pozyz inner algorithm with a range accuracy of 320 ± 30 mm. In [23], to locate underground personnel in coal mines, an UWB wireless sensor network and time difference of arrival (TDOA) algorithm was proposed, and this system can achieve high-precision positioning in real-time. Furthermore, in the nondestructive environment, direct sequence ultra-wide band (DS-UWB) transmission system with an adaptive pseudo random sequence length is proposed in [24] to reduce processing time and increase positioning accuracy. As mentioned above, the PPM modulation is widely applied to the UWB system, especially for detecting the location of objects; however, the accuracy of estimated results is still low. In this paper, we focus on proposing a new modulation scheme based on PPM modulation to improve the resolution of the estimated distance. The main contributions of this research are listed as follows.


The remainder of this paper is organized as follows. Section 2 describes the system model for estimating distances in nondestructive environments. The proposed system model and the parameters are presented in Section 3. The simulation results are provided in Section 4, and finally, conclusions and further work are discussed in Section 5.
