Based on the zero correlation zone (ZCZ) concept, we present the definitions and properties of a set of new ternary codes, ZCZ sequencePair Set (ZCZPS), and propose a method to use the optimized punctured sequencepair along with Hadamard matrix to construct an optimized punctured ZCZ sequencepair set (OPZCZPS) which has ideal autocorrelation and crosscorrelation properties in the zero correlation zone. Considering the moving target radar system, the correlation properties of the codes will not be severely affected when Doppler shift is not large. We apply the proposed codes as pulse compression codes to radar system and the simulation results show that optimized punctured ZCZ sequencepairs outperform other conventional pulse compression codes, such as the wellknown polyphase code—P4 code.
1. Introduction
Pulse compression is known as a technique to raise the signal to maximum sidelobe (signaltosidelobe) ratio to improve the target detection and range resolution abilities of the radar system. This technique allows a radar to simultaneously achieve the energy of a long pulse and the resolution of a short pulse without the high peak power which is required by a high energy short duration pulse [1]. One of the waveform designs suitable for pulse compression is phasecoded waveform design. The phasecoded waveform design is that a long pulse of duration is divided into subpulses each of width . Each subpulse has a particular phase, which is selected in accordance with a given code sequence. The pulse compression ratio equals the number of subpulses , where the bandwidth is . In general, a phasecoded waveform with longer code word, in other words, higher pulse compression ratio, can have lower sidelobe of autocorrelation, relative to the mainlobe peak, so its main peak can be better distinguished. The relative lower sidelobe of autocorrelation is very important since range sidelobes are so harmful that they can mask main peaks caused by small targets situated near large targets. In addition, the crosscorrelation property of the pulse compression codes should be considered in order to reduce the interference among radars when we choose a set of pulse compression codes to work in a Radar Sensor Network (RSN).
Much time and effort was put for designing sequences with impulsive autocorrelation functions (ACFs) and crosscorrelation functions (CCFs) for radar target ranging and target detection. On one hand, for aperiodic sequences, it is known that for most binary sequences of length the attainable sidelobe levels are approximately [2, 3] and the mutual peak crosscorrelations of the samelength sequences are much larger and are usually in the order of to . Later, set of binary sequences of length with autocorrelation sidelobes and crosscorrelation peak values of approximately are studied in paper [4]. Besides, the small set of Kasami sequences and the Bent sequences could achieve maximum correlation values of approximately . In addition to binary sequences, polyphase codes, with better Doppler tolerance and lower range sidelobes such as the Frank and P1 codes, the Butlermatrix derived P2 code, the linearfrequencyderived P3 and P4 codes were provided and intensively analyzed in [5–7]. Quadiphase [8] code could also reduce poor falloff of the radiated spectrum and mismatch loss in the receiver pulse compression filter of biphase codes. Nevertheless, the range sidelobe of the polyphase codes can not be low enough to avoid masking returns from targets. Hence, considerable work has been done to reduce range sidelobes for the radar system. By suffering a small loss, the authors in [9] present several binary pulse compression codes to greatly reduce sidelobes. In the previous paper [10], pulse compression using a digitalanalog hybrid technique is studied to achieve very low range sidelobes for potential application to spaceborne rain radar. In the paper [11], timedomain weighting of the transmitted pulse is used and is able to achieve a range sidelobe level of 55 dB or better in flight tests. These sidelobe suppression methods, however, degrade the receiving resolution because of wider mainlobe.
On the other hand, for periodic sequences, the lowest periodic ACF that could be achieved for binary sequences, as in the case of sequences [12, 13] or Legendre sequences, is . GMW [14] has the same periodic ACF properties, but posses larger linear complexity. Considering the nonbinary case, it is possible to find perfect sequences, such as two valued Golomb sequences, Ipatov ternary sequences, Frank sequences, Chu sequences, and modulatable sequences. However, it should be noted that for both binary and nonbinary cases, it is impossible for the sequences to have perfect ACF and CCF simultaneously although ideal CCFs could be achieved alone. One can synthesize a set of nonbinary sequences with impulsive ACF and the lower bound of CCF: , [15, 16], which is governed by Welch bound and Sidelnikov bound.
So far in the previous work, range sidelobes could hardly reach as low as zero. In addition, it has also been well proven that it is impossible to design a set of codes with ideal impulsive autocorrelation function and ideal zero crosscorrelation functions, since the corresponding parameters have to be limited by certain bounds, such as Welch bound [15], Sidelnikov bound [16], Sarwate bound [17], and Levenshtein bound [18]. To overcome these difficulties, the new concepts, generalized orthogonality (GO), also called Zero Correlation Zone (ZCZ) is introduced. Based on ZCZ [19–21] concept, we propose a set of ternary codes, ZCZ sequencepair set, which can reach zero autocorrelation sidelobe zero mutual crosscorrelation peaks during Zero Correlation Zone. We also present and analyze a method to construct such ternary codes and subsequently apply them to a radar detection system. The method is that optimized punctured sequencepair joins together with Hadamard matrix to construct optimized punctured ZCZ sequencepairs set. An example is presented, investigated, and studied in the radar targets detection simulation system for the performance evaluation of the proposed ternary codes. Because of the outstanding property performance and well target detection performance in simulation system, the newly proposed codes can be useful candidates for pulse compression application in radar system.
The rest of the paper is organized as follows. Section 2 introduces the definitions and properties of ZCZPS. In Section 3, the optimized punctured ZCZPS is introduced, and a method using optimized punctured sequencepair and Hadamard matrix to construct such codes is given and proved. In Section 4, the properties and ambiguity function of optimized punctured ZCZPS are simulated and analyzed. The performance of optimized punctured ZCZPS is investigated in radar targets detection system by comparing with P4 code in Section 5. In Section 6, conclusions are drawn on optimized punctured ZCZPS.
2. Definitions and Properties of ZCZ SequencePair Set
Zero Correlation Zone (ZCZ) is a new concept provided by Fan et al. [21, 22] in which the autocorrelation sidelobes and crosscorrelation values are zero while the time delay is kept within ZCZ instead of the whole period of time domain. There has been considerable interest in constructing [23–27] new classes of ZCZ sequences in ZCZ and studying their properties [28].
Here, we introduce sequencepair into the ZCZ concept to construct ZCZ sequencepair set. We consider ZCZPS , is a set of sequences of length and is a set of sequences of the same length :
The autocorrelation function (ACF) (here we use autocorrelation to stand for the crosscorrelation between two different sequences of a sequencepair to distinguish the crosscorrelation between two different sequencepairs) of sequencepair is defined by
The crosscorrelation function of two sequencepairs and , is defined by
where is the time delay and is the bit duration.
For pulse compression sequences, some properties are of particular concern in the optimization for any design in engineering field. They are the peak sidelobe level, the energy of autocorrelation sidelobes, and the energy of their mutual crosscorrelation [4]. Therefore, the peak sidelobe level which represents a source of mutual interference and obscures weaker targets can be presented as , is among the zero correlation zone for ZCZPS. Another optimization criterion for the set of sequencepairs is the energy of autocorrelation sidelobes joined together with the energy of crosscorrelation. By minimizing the energy, it can be distributed evenly, and the peak autocorrelation sidelobe and the crosscorrelation level can be minimized as well [4]. Here, the energy of ZCZPS can be employed as
According to (4), it is obvious to see that the energy can be kept low while minimizing the autocorrelation sidelobes and crosscorrelation values of any two sequencepairs within Zero Correlation Zone.
Hence, the ZCZPS can be constructed by minimizing the autocorrelation sidelobe of a sequencepair and crosscorrelation value of any two sequencepairs in ZCZPS.
Definition 1.
Assume to be a sequencepair set of sequencepairs and each sequencepair is of bit length. If all the sequencepairs in the set satisfy the following equation:
where , , and . Then is called a ZCZ sequencepair, is an abbreviation, and is called a ZCZ sequencepair set, is an abbreviation.
3. Optimized Punctured ZCZ SequencePair Set
3.1. Definition of Optimized Punctured ZCZ SequencePair Set
Matsufuji and Torii have provided some methods of constructing ZCZ sequences in [29, 30]. In this section, a set of novel ternary codes, namely, the optimized punctured ZCZ sequencepair set, is constructed by applying the optimized punctured sequencepair [31] to the Zero Correlation Zone. Here, optimized punctured ZCZPS is a specific kind of ZCZPS.
Definition 2 (see [31]).
Sequence is the punctured sequence for
where is the number of punctured bits in sequence . Suppose and , is punctured binary sequence, is called a punctured binary sequencepair.
Definition 3 (see [31]).
The autocorrelation of punctured sequencepair is defined as
If the punctured sequencepair has the following autocorrelation property:
the punctured sequencepair is called an optimized punctured sequencepair [31]. Where, , is the energy of punctured sequencepair.
Definition 4.
If in Definition 1 is constructed by optimized punctured sequencepair and a certain matrix, such as Hadamard matrix or an orthogonal matrix, where
Then
where and , then can be called an optimized punctured ZCZ sequencepair set. is an abbreviation.
3.2. Design of Optimized Punctured ZCZ SequencePair Set
Based on an optimized punctured binary sequencepair of odd length and a Hadamard matrix, an optimized punctured ZCZPS can be constructed on following steps.
Step 1.
Considering an optimized punctured binary sequencepair of odd length, the length of each sequence is :
Step 2.
A Hadamard matrix (the Hadamard matrix is made up of a set of Walsh sequences) of order is used here. , the length of each sequence, is equal to the number of the sequences in the matrix. Here, any Hadamard matrix order is possible and is the row vector of the matrix:
Step 3.
Doing bitmultiplication on the optimized punctured binary sequencepair and each row of the Hadamard matrix B, then sequencepair set is obtained,
Here, the optimized punctured binary sequencepairs are of odd lengths and the lengths of Walsh sequence are , It is easy to see that , common divisor of and is 1, then . The sequencepair set is the optimized punctured ZCZPS and is the Zero Correlation Zone . The length of each sequence in optimized punctured ZCZPS is that depends on the product of length of optimized punctured sequencepair and the length of Walsh sequence in Hadamard matrix. The number of sequencepairs in optimized punctured ZCZPS rests on the order of the Hadamard matrix. The sequence in sequence set and the corresponding sequence in sequence set construct a sequencepair that can be used as a pulse compression code.
The correlation property of the sequencepairs in optimized punctured ZCZPS is
where is the Zero Correlation Zone and .
Proof.
() When ,
() When ,
According to Definition 1, the OPZCZPS constructed by the above method is a ZCZPS.
4. Properties of Optimized Punctured ZCZ SequencePair Set
Considering the optimized punctured ZCZPS constructed by the method mentioned in the last section, the autocorrelation and crosscorrelation properties can be simulated and analyzed. For example, the optimized punctured ZCZPS is constructed by 31length optimized punctured binary sequencepair , , (using "'' and "'' symbols for "'' and "'') and Hadamard matrix of order 4. We follow the three steps presented in Section 3.2 to construct the optimized punctured ZCZPS. The number of sequencepairs here is 4, and the length of each sequence is . The first row of each matrix and constitute a certain optimized punctured ZCZP . Similarly, the second row of each matrix and constitute another optimized punctured ZCZ sequencepair , and so on:
Here, optimized punctured ZCZ sequencepairs and are studied as two examples in the following parts.
4.1. Autocorrelation and CrossCorrelation Properties
The autocorrelation property and crosscorrelation property of 124length sequencepairs in the optimized punctured ZCZ sequencepair set are shown in Figures 1 and 2.
Figure 1. Periodic autocorrelation property of optimized punctured ZCZPS.
Figure 2. Periodic crosscorrelation property of optimized punctured ZCZPS.
From the Figures 1 and 2, the peak autocorrelation sidelobe of ZCZPS and their crosscorrelation value are kept as low as zero while the time delay is kept within (Zero Correlation Zone). And it is always true that the crosscorrelation values of optimized punctured ZCZPS and the autocorrelation sidelobe could be kept as low as zero during ZCZ.
We still have to confess that the energy loss of the proposed codes is no less than 1.7 db due to reference mismatch. However, the perfect periodic ACF and CCF achieved simultaneously during the ZCZ zone and the codes' structure could make up for it. It is known that a suitable criterion for evaluating code of length is the ratio of the peak signal mainlobe divided by the peak signal sidelobe (PSR) of their autocorrelation function, which can be bounded by [32]
The only aperiodic uniform phase codes that can reach the are the Barker codes whose length is equal or less than 13. Considering the periodic sequences, the sequences or Legendre sequences could achieve the lowest periodic ACF of . For nonbinary sequences, it is possible to find perfect sequences of ideal ACF. Golomb codes are a kind of two valued (biphase) perfect codes which obtain zero periodic ACF but result in large mismatch power loss. The Ipatov code shows a way of designing code pairs with perfect periodic autocorrelation (the crosscorrelation of the code pair) and minimal mismatch loss. In addition, zero periodic autocorrelation function for all nonzero shifts could be obtained by polyphase codes, such as Frank and Zadoff codes. However, for both binary and nonbinary periodic sequences, it is not possible for the sequences to have perfect ACF and CCF simultaneously although ideal CCFs could be achieved alone. Comparing with the above codes, the proposed ternary codes could obtain perfect periodic ACF during the ZCZ and the reference sequence is made of which is much less complicated than other perfect ternary codes such as Ipatvo code. The reference code for Ipatov code is of a threeelement alphabet which might not always be integer.
Nevertheless, considering multi targets in the system, multiple peaks of the autocorrelation function of the proposed codes might affect on the range resolution. The range resolution could be limited as or . Here, is one bit duration, is the length of an optimized punctured sequencepair and is the length of an optimized punctured ZCZ sequencepair. In the Figure 1, . Otherwise, some digital signal processing methods could also be introduced to distinguish the peaks. On the other hand, there may also be the concern that multiple peaks of single transmitting signal reflected from one target may affect determining the main peak of ACF. As a matter of fact, the matched filter here could shift at the period of ZCZ length to track each peak instead of shifting bit by bit after the first peak is acquired. Hence, in this way could it be working more efficiently. Alike the tracking technology in synchronization of CDMA system, checking several peaks instead of only one peak guarantee the precision of and avoidance of . In addition, those obtained peaks could be averaged before the detection in order to reduce the effect of random noise in the channel so that the detection performance could be improved.
To sum up, the new code could achieve perfect ACF and CCF in the ZCZ simultaneously according to Figures 1 and 2, and its PSR can be as large as infinite.
4.2. Ambiguity Function
When the transmitted impulse is reflected by a moving target, the reflected echo signal includes a linear phase shift which corresponds to a Doppler shift [32]. As a result of the Doppler shift , the main peak of the autocorrelation function is reduced. The SNR is degraded and the sidelobe structure is also changed because of the Doppler shift.
The ambiguity function which is usually used to analyze the radar performance within Doppler shift and time delay is defined in [32]:
where is the time delay between transmitting signal and matched filter, and is the Doppler shift.
In [33], Periodic Ambiguity Function (PAF) is introduced by Levanon as an extension of the periodic autocorrelation for Doppler shift. And the singleperiodic complex envelope is [34]
where is one period of the signal.
We are studying sequencepairs in this research, so we use different codes for transmitting part and receiving part. The singleperiod ambiguity function for ZCZPS can be rewritten as
where , is one period of the signal and is one bit duration. At the same time, when , (21) can be used to analyze the autocorrelation property within Doppler shift, and when , (21) can be used to analyze the crosscorrelation performance within Doppler shift. Equation (21) is plotted in Figure 3 in a threedimensional surface plot to analyze the radar performance of optimized punctured ZCZPS within Doppler shift. Here, maximal time delay is 1 unit (normalized to length of the code, in units of ) and maximal Doppler shift is 5 units for crosscorrelation and 3 units for autocorrelation (normalized to the inverse of the length of the code, in units of ).
Figure 3. Ambiguity function of 124length ZCZPS: (a) autocorrelation, (b) crosscorrelation.
In Figure 3(a), there is relative uniform plateau suggesting low and uniform sidelobes. This low and uniform sidelobes minimize target masking effect in Zero Correlation Zone of time domain, where , . From Figure 3(b), considering crosscorrelation property between any two optimized punctured ZCZ sequencepairs of the ZCZPS, we can see that the optimized punctured ZCZPS is tolerant of Doppler shift when Doppler shift is not large. When the Doppler shift is zero, or the target is not moving, crosscorrelation of our proposed code is zero during ZCZ.
Since synchronizing techniques develop exponentially in the industrial world, time delay between transmitting signal and matched filter can, to some extent, be precisely estimated. Therefore, it is necessary to investigate the property of our proposed code when we have the output of the matched filter at the expected time . When , the ambiguity function can be expressed as
And the Doppler shift performance without time delay is presented in the Figure 4.
Figure 4. Doppler shift of 124length ZCZPS (): (a) autocorrelation (b) crosscorrelation.
Figure 4(a) illustrates that without time delay of matched filter but having the Doppler shift less than 1 unit, the autocorrelation value of optimized punctured ZCZPS falls sharply during one unit, and the trend of the amplitude over the whole frequency domain decreases as well. Figure 4(b) shows that there are some convex surfaces in the crosscorrelation performance. From Figures 4(a) and 4(b), when Doppler frequencies equal to multiples of the pulse repetition frequency (), all the ambiguity values turn to zero except when Doppler frequency is equal to 2 PRF for crosscorrelation. That is the same as many widely used pulse compression binary code such as the Barker code. Overall, the ambiguity function performances of optimized punctured ZCZP can be as efficient as conventional pulse compression binary code.
5. Application to Radar System
According to [32], Probability of Detection (), Probability of False Alarm () and Probability of Miss () are three probabilities of most interest in the radar system. Note that . Therefore, we simulated the above three probabilities of using 124length optimized punctured ZCZ sequencepair in radar system in this section. The performance of radar system using 124length P4 code is also studied in order to compare with the performance of optimized punctured ZCZ sequencepairs of corresponding length. In the simulation model, times of MonteCarlo simulation has been run for each SNR value. The Doppler shift frequency is a random variable that is kept less than 1 unit (normalized to the inverse of the length of the code, in units of ), and the expected peak time of the output of the matched filter is at .
From Figure 5, the probabilities of miss target detection of the system using 124length optimized punctured ZCZP are lower than 124length P4 code especially when the SNR is not high. When SNR is higher than 18 dB, both probabilities of miss targets of the system approach zero. However, the probabilities of miss targets of P4 code fall more quickly than optimized punctured ZCZP.
Figure 5. Probability of miss targets detection: 124length optimized punctured ZCZ sequencepair versus 124length P4 code.
We plotted the detection probability versus false alarm probability of the coherent receiver. We have simulated the performance at different SNR values. Because of the limited space, we only chose SNR at 12 db and 14 dB. Figure 6 shows performance of 124length optimized punctured ZCZP and performance of the same length P4 code when the SNR is 12 dB and 14 dB. Within the same SNR value either 12 dB or 14 dB, the detection probabilities of optimized punctured ZCZ sequencepair are much larger than detection probabilities of P4 code, and meanwhile of the first code are also smaller than of the latter code. Stating differently, optimized punctured ZCZ sequencepair has higher target detection probability while keeping a lower false alarm probability. Furthermore, observing Figure 6, 124length optimized punctured ZCZ sequencepair even has much better performance at 12 dB SNR than P4 code of corresponding length at 14 dB SNR.
Figure 6. Probability of detection versus probability of false alarm of the coherent receiver: 124length optimized punctured ZCZ sequencepair versus 124length P4 code.
6. Conclusions
The definition and properties of a set of newly provided ternary codesZCZ sequencepair set were discussed in this paper. Based on optimized punctured sequencepair and Hadamard matrix, we have investigated a constructing method for a specific ZCZPSoptimized punctured ZCZPS made up of a set of optimized punctured ZCZPs along with studying its properties. The significant advantage of the optimized punctured ZCZPS is the considerably reducedn autocorrelation sidelobe and zero mutual crosscorrelation value during ZCZ. According to the radar system simulation results shown in Figures 5 and 6, it is easy to observe that 124length optimized punctured ZCZPS has better performance than P4 code of the same length when the target is not moving very fast in the system. A general conclusion can be drawn that the optimized punctured ZCZPS consisting of optimized punctured ZCZ sequencepairs can effectively increase the variety of candidates for pulse compression codes. Because of the ideal crosscorrelation properties of optimized punctured ZCZPS, our future work would focus on the application of the optimized punctured ZCZPS in multiple radar systems.
Acknowledgments
This work was supported in part by the National Science Foundation under Grants CNS0721515, CNS 0831902, CCF0956438, CNS0964713, and Office of Naval Research (ONR) under Grant N000140710395 and N000140711024.
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